Randomized kd-tree index. More...

#include <opencv2/flann/kdtree_index.h>

Inheritance diagram for cvflann::KDTreeIndex< Distance >:

Collaboration diagram for cvflann::KDTreeIndex< Distance >:

Public Types
typedef Distance::ResultType	DistanceType

typedef Distance::ElementType	ElementType

Public Member Functions
	KDTreeIndex (const Matrix< ElementType > &inputData, const IndexParams &params=KDTreeIndexParams(), Distance d=Distance())
	KDTree constructor. More...

	KDTreeIndex (const KDTreeIndex &)

	~KDTreeIndex ()
	Standard destructor. More...

void	buildIndex () CV_OVERRIDE
	Builds the index. More...

void	findNeighbors (ResultSet< DistanceType > &result, const ElementType *vec, const SearchParams &searchParams) CV_OVERRIDE
	Find set of nearest neighbors to vec. More...

IndexParams	getParameters () const CV_OVERRIDE

flann_algorithm_t	getType () const CV_OVERRIDE

virtual void	knnSearch (const Matrix< ElementType > &queries, Matrix< int > &indices, Matrix< DistanceType > &dists, int knn, const SearchParams &params)
	Perform k-nearest neighbor search. More...

void	loadIndex (FILE *stream) CV_OVERRIDE
	Loads the index from a stream. More...

KDTreeIndex &	operator= (const KDTreeIndex &)

virtual int	radiusSearch (const Matrix< ElementType > &query, Matrix< int > &indices, Matrix< DistanceType > &dists, float radius, const SearchParams &params)
	Perform radius search. More...

void	saveIndex (FILE *stream) CV_OVERRIDE
	Saves the index to a stream. More...

size_t	size () const CV_OVERRIDE
	Returns size of index. More...

int	usedMemory () const CV_OVERRIDE
	Computes the inde memory usage Returns: memory used by the index. More...

size_t	veclen () const CV_OVERRIDE
	Returns the length of an index feature. More...

Detailed Description

template<typename Distance>
class cvflann::KDTreeIndex< Distance >

Randomized kd-tree index.

Contains the k-d trees and other information for indexing a set of points for nearest-neighbor matching.

Member Typedef Documentation

◆ DistanceType

template<typename Distance>

typedef Distance::ResultType cvflann::KDTreeIndex< Distance >::DistanceType

◆ ElementType

template<typename Distance>

typedef Distance::ElementType cvflann::KDTreeIndex< Distance >::ElementType

Constructor & Destructor Documentation

◆ KDTreeIndex() [1/2]

template<typename Distance>

cvflann::KDTreeIndex< Distance >::KDTreeIndex	(	const Matrix< ElementType > &	inputData,
		const IndexParams &	params = `KDTreeIndexParams()`,
		Distance	d = `Distance()`
	)

inline

KDTree constructor.

Params: inputData = dataset with the input features params = parameters passed to the kdtree algorithm

References cvflann::get_param().

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◆ KDTreeIndex() [2/2]

template<typename Distance>

cvflann::KDTreeIndex< Distance >::KDTreeIndex ( const KDTreeIndex< Distance > & )

◆ ~KDTreeIndex()

template<typename Distance>

cvflann::KDTreeIndex< Distance >::~KDTreeIndex ( )

inline

Standard destructor.

Member Function Documentation

◆ buildIndex()

template<typename Distance>

void cvflann::KDTreeIndex< Distance >::buildIndex ( )

inlinevirtual

Builds the index.

Implements cvflann::NNIndex< Distance >.

References cv::randShuffle().

Referenced by cvflann::AutotunedIndex< Distance >::getType().

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◆ findNeighbors()

template<typename Distance>

void cvflann::KDTreeIndex< Distance >::findNeighbors	(	ResultSet< DistanceType > &	result,
		const ElementType *	vec,
		const SearchParams &	searchParams
	)

inlinevirtual

Find set of nearest neighbors to vec.

Their indices are stored inside the result object.

Params: result = the result object in which the indices of the nearest-neighbors are stored vec = the vector for which to search the nearest neighbors maxCheck = the maximum number of restarts (in a best-bin-first manner)

Implements cvflann::NNIndex< Distance >.

References cvflann::FLANN_CHECKS_UNLIMITED, and cvflann::get_param().

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◆ getParameters()

template<typename Distance>

IndexParams cvflann::KDTreeIndex< Distance >::getParameters ( ) const

inlinevirtual

Returns: The index parameters

Implements cvflann::NNIndex< Distance >.

References cvflann::ResultSet< DistanceType >::addPoint(), cvflann::ResultSet< DistanceType >::full(), cvflann::Heap< T >::insert(), cvflann::load_value(), cv::min(), cvflann::BranchStruct< T, DistanceType >::mindist, cvflann::BranchStruct< T, DistanceType >::node, cvflann::Heap< T >::popMin(), cvflann::rand_int(), cvflann::save_value(), cvflann::DynamicBitset::set(), cv::swap(), cvflann::DynamicBitset::test(), and cvflann::ResultSet< DistanceType >::worstDist().

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◆ getType()

template<typename Distance>

flann_algorithm_t cvflann::KDTreeIndex< Distance >::getType ( ) const

inlinevirtual

Returns: The index type (kdtree, kmeans,...)

Implements cvflann::NNIndex< Distance >.

References cvflann::FLANN_INDEX_KDTREE.

◆ knnSearch()

template<typename Distance>

virtual void cvflann::NNIndex< Distance >::knnSearch	(	const Matrix< ElementType > &	queries,
		Matrix< int > &	indices,
		Matrix< DistanceType > &	dists,
		int	knn,
		const SearchParams &	params
	)

inlinevirtualinherited

Perform k-nearest neighbor search.

Parameters

[in]	queries	The query points for which to find the nearest neighbors
[out]	indices	The indices of the nearest neighbors found
[out]	dists	Distances to the nearest neighbors found
[in]	knn	Number of nearest neighbors to return
[in]	params	Search parameters

Reimplemented in cvflann::Index< Distance >, cvflann::Index< cv::L2< ElementType > >, cvflann::Index< cv::L1< ElementType > >, cvflann::KDTreeSingleIndex< Distance >, and cvflann::LshIndex< Distance >.

◆ loadIndex()

template<typename Distance>

void cvflann::KDTreeIndex< Distance >::loadIndex ( FILE * stream )

inlinevirtual

Loads the index from a stream.

Parameters

stream The stream from which the index is loaded

Implements cvflann::NNIndex< Distance >.

References cvflann::load_value().

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◆ operator=()

template<typename Distance>

KDTreeIndex& cvflann::KDTreeIndex< Distance >::operator= ( const KDTreeIndex< Distance > & )

◆ radiusSearch()

template<typename Distance>

virtual int cvflann::NNIndex< Distance >::radiusSearch	(	const Matrix< ElementType > &	query,
		Matrix< int > &	indices,
		Matrix< DistanceType > &	dists,
		float	radius,
		const SearchParams &	params
	)

inlinevirtualinherited

Perform radius search.

Parameters

[in]	query	The query point
[out]	indices	The indinces of the neighbors found within the given radius
[out]	dists	The distances to the nearest neighbors found
[in]	radius	The radius used for search
[in]	params	Search parameters

Returns: Number of neighbors found

Reimplemented in cvflann::Index< Distance >, cvflann::Index< cv::L2< ElementType > >, and cvflann::Index< cv::L1< ElementType > >.

◆ saveIndex()

template<typename Distance>

void cvflann::KDTreeIndex< Distance >::saveIndex ( FILE * stream )

inlinevirtual

Saves the index to a stream.

Parameters

stream The stream to save the index to

Implements cvflann::NNIndex< Distance >.

References cvflann::save_value().

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◆ size()

template<typename Distance>

size_t cvflann::KDTreeIndex< Distance >::size ( ) const

inlinevirtual

Returns size of index.

Implements cvflann::NNIndex< Distance >.

◆ usedMemory()

template<typename Distance>

int cvflann::KDTreeIndex< Distance >::usedMemory ( ) const

inlinevirtual

Computes the inde memory usage Returns: memory used by the index.

Implements cvflann::NNIndex< Distance >.

Referenced by cvflann::AutotunedIndex< Distance >::getType().

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◆ veclen()

template<typename Distance>

size_t cvflann::KDTreeIndex< Distance >::veclen ( ) const

inlinevirtual

Returns the length of an index feature.

Implements cvflann::NNIndex< Distance >.

The documentation for this class was generated from the following file:

opencv2/flann/kdtree_index.h

Public Types

Public Member Functions

Detailed Description

template<typename Distance> class cvflann::KDTreeIndex< Distance >

Member Typedef Documentation

◆ DistanceType

◆ ElementType

Constructor & Destructor Documentation

◆ KDTreeIndex() [1/2]

◆ KDTreeIndex() [2/2]

◆ ~KDTreeIndex()

Member Function Documentation

◆ buildIndex()

◆ findNeighbors()

◆ getParameters()

◆ getType()

◆ knnSearch()

◆ loadIndex()

◆ operator=()

◆ radiusSearch()

◆ saveIndex()

◆ size()

◆ usedMemory()

◆ veclen()

template<typename Distance>
class cvflann::KDTreeIndex< Distance >