cvflann::L1< T > Struct Template Reference

OpenCV 4.1.0

Open Source Computer Vision

#include <opencv2/flann/dist.h>

Public Types
typedef T	ElementType

typedef True	is_kdtree_distance

typedef True	is_vector_space_distance

typedef Accumulator< T >::Type	ResultType

Public Member Functions
template<typename U , typename V >
ResultType	accum_dist (const U &a, const V &b, int) const

template<typename Iterator1 , typename Iterator2 >
ResultType	operator() (Iterator1 a, Iterator2 b, size_t size, ResultType worst_dist=-1) const

Member Typedef Documentation

template<class T >

typedef T cvflann::L1< T >::ElementType

template<class T >

typedef True cvflann::L1< T >::is_kdtree_distance

template<class T >

typedef True cvflann::L1< T >::is_vector_space_distance

template<class T >

typedef Accumulator<T>::Type cvflann::L1< T >::ResultType

Member Function Documentation

template<class T >

template<typename U , typename V >

ResultType cvflann::L1< T >::accum_dist	(	const U &	a,
		const V &	b,
		int
	)		const

inline

Partial distance, used by the kd-tree.

template<class T >

template<typename Iterator1 , typename Iterator2 >

ResultType cvflann::L1< T >::operator()	(	Iterator1	a,
		Iterator2	b,
		size_t	size,
		ResultType	worst_dist = `-1`
	)		const

inline

Compute the Manhattan (L_1) distance between two vectors.

This is highly optimised, with loop unrolling, as it is one of the most expensive inner loops.

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

dist.h