OpenCV  2.4.13.4
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cvflann::KDTreeIndex< Distance > Class Template Reference

#include <kdtree_index.h>

Inheritance diagram for cvflann::KDTreeIndex< Distance >:
cvflann::NNIndex< Distance >

Public Types

typedef Distance::ElementType ElementType
 
typedef Distance::ResultType DistanceType
 

Public Member Functions

 KDTreeIndex (const Matrix< ElementType > &inputData, const IndexParams &params=KDTreeIndexParams(), Distance d=Distance())
 
 KDTreeIndex (const KDTreeIndex &)
 
KDTreeIndex & operator= (const KDTreeIndex &)
 
 ~KDTreeIndex ()
 
void addIndex (const Matrix< ElementType > &, const Matrix< ElementType > &)
 
void buildIndex ()
 
flann_algorithm_t getType () const
 
void saveIndex (FILE *stream)
 Saves the index to a stream. More...
 
void loadIndex (FILE *stream)
 Loads the index from a stream. More...
 
size_t size () const
 
size_t veclen () const
 
int usedMemory () const
 
void findNeighbors (ResultSet< DistanceType > &result, const ElementType *vec, const SearchParams &searchParams)
 
IndexParams getParameters () const
 
- Public Member Functions inherited from cvflann::NNIndex< Distance >
virtual ~NNIndex ()
 
virtual void knnSearch (const Matrix< ElementType > &queries, Matrix< int > &indices, Matrix< DistanceType > &dists, int knn, const SearchParams &params)
 Perform k-nearest neighbor search. More...
 
virtual int radiusSearch (const Matrix< ElementType > &query, Matrix< int > &indices, Matrix< DistanceType > &dists, float radius, const SearchParams &params)
 Perform radius search. 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

§ 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

§ addIndex()

template<typename Distance>
void cvflann::KDTreeIndex< Distance >::addIndex ( const Matrix< ElementType > &  ,
const Matrix< ElementType > &   
)
inlinevirtual

Dummy implementation for other algorithms of addable indexes after that.

Implements cvflann::NNIndex< Distance >.

§ buildIndex()

template<typename Distance>
void cvflann::KDTreeIndex< Distance >::buildIndex ( )
inlinevirtual

Builds the index

Implements cvflann::NNIndex< Distance >.

§ 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 >.

§ getParameters()

template<typename Distance>
IndexParams cvflann::KDTreeIndex< Distance >::getParameters ( ) const
inlinevirtual
Returns
The index parameters

Implements cvflann::NNIndex< Distance >.

§ getType()

template<typename Distance>
flann_algorithm_t cvflann::KDTreeIndex< Distance >::getType ( ) const
inlinevirtual
Returns
The index type (kdtree, kmeans,...)

Implements cvflann::NNIndex< Distance >.

§ loadIndex()

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

Loads the index from a stream.

Parameters
streamThe stream from which the index is loaded

Implements cvflann::NNIndex< Distance >.

§ operator=()

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

§ saveIndex()

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

Saves the index to a stream.

Parameters
streamThe stream to save the index to

Implements cvflann::NNIndex< Distance >.

§ 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 >.

§ 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: