tw Namespace Reference

namespace tw is mostly related to some utility functions developed by the repository owner, Tianwei Shen. More...

Classes
class	IO
	To safely read and write files. More...
class	SiftData
	Sift data structure used in libvot. More...
class	UnionFind
	Union-find data structure, used in various graph algorithms. More...
struct	VlFeatParam
	a parameter struct used in calling vlfeat sift function More...
struct	Vlfeature
	a struct containing the data of vlfeat features More...

Functions
bool	OpencvKeyPoints2libvotSift (std::vector< cv::KeyPoint > &key_points, cv::Mat &descriptors, tw::SiftData &sift_data)
bool	Vlfeature2LibvotSift (std::vector< Vlfeature > const &vlfeature_vec, unsigned char const *data, int image_width, int image_height, int num_channel, tw::SiftData &sift_data)
void	VlFeatureDetection (unsigned char const *data, std::vector< Vlfeature > &vlfeature_vec, int image_width, int image_height, VlFeatParam const &vlfeat_param)
int	RunVlFeature (unsigned char *data, int image_width, int image_height, int num_channel, SiftData &sift_data, VlFeatParam const &vlfeat_param)
template<typename T >
T *	allocate_2d (T ***array, int row, int col)
template<typename T >
void	free_2d (T ***array, T *data)
template int *	allocate_2d< int > (int ***array, int row, int col)
template void	free_2d< int > (int ***array, int *data)
template float *	allocate_2d< float > (float ***array, int row, int col)
template void	free_2d< float > (float ***array, float *data)
template double *	allocate_2d< double > (double ***array, int row, int col)
template void	free_2d< double > (double ***array, double *data)
template vot::LinkEdge *	allocate_2d< vot::LinkEdge > (vot::LinkEdge ***array, int row, int col)
template void	free_2d< vot::LinkEdge > (vot::LinkEdge ***array, vot::LinkEdge *data)
void	GetIntialCenters (size_t n, int k, size_t *initial_idx)
void	CopyDes2Double (double *dst, DTYPE *src, int length)
double	DisDes2Double (double *dst, DTYPE *src, int length)
void	MultiComputeAssignment (size_t num, int dim, int k, DTYPE **des, double *means, int *assignment, double *error_out, size_t *changed_num)
size_t	ComputeAssignment (size_t num, int dim, int k, DTYPE **p, double *means, int *assignment, double &error_out, int thread_num)
	Compute new assignment for each feature points. More...
void	MultiDesAccumulation (size_t num, int dim, int k, DTYPE **p, int *assignment_curr, double *totals, size_t *counts)
	Accumulate the feature descriptors to the total, a subroutine used by multi-threaded version of ComputeMeans. More...
void	ComputeMeans (size_t num, int dim, int k, DTYPE **p, int *assignment_curr, double *means_curr, int thread_num)
	Compute new means for each cluster. More...
double	ComputeError (size_t num, int dim, int k, DTYPE **p, double *means, int *assignment)
double	Kmeans (size_t num, int dim, int k, DTYPE **p, double *means, int *assignment, int thread_num)

Detailed Description

namespace tw is mostly related to some utility functions developed by the repository owner, Tianwei Shen.

It includes some utility classes and functions, such as the file I/O class.

Function Documentation

template<typename T >

T * tw::allocate_2d	(	T ***	arr,
		int	row,
		int	col
	)

allocate a continuous 2d array

template double* tw::allocate_2d< double >	(	double ***	array,
		int	row,
		int	col
	)

template float* tw::allocate_2d< float >	(	float ***	array,
		int	row,
		int	col
	)

template int* tw::allocate_2d< int >	(	int ***	array,
		int	row,
		int	col
	)

template vot::LinkEdge* tw::allocate_2d< vot::LinkEdge >	(	vot::LinkEdge ***	array,
		int	row,
		int	col
	)

size_t tw::ComputeAssignment	(	size_t	num,
		int	dim,
		int	k,
		DTYPE **	p,
		double *	means,
		int *	assignment,
		double &	error_out,
		int	thread_num
	)

Compute new assignment for each feature points.

Parameters

num	- the total number of feature points
dim	- the dimension of the feature points
k	- the number of clusters
p	- the address to the feature points
means	- the descriptors of the clusters
assignment	- the input and output assignments
error	- total error of the new assignment
thread_num	- thread number

Returns

double tw::ComputeError	(	size_t	num,
		int	dim,
		int	k,
		DTYPE **	p,
		double *	means,
		int *	assignment
	)

void tw::ComputeMeans	(	size_t	num,
		int	dim,
		int	k,
		DTYPE **	p,
		int *	assignment_curr,
		double *	means_curr,
		int	thread_num
	)

Compute new means for each cluster.

Parameters

num	- the total number of feature points
dim	- the dimension of the feature points
k	- the number of clusters
assignment_curr	- the current assignments computed by ComputeAssignment
means_curr	- the means of clusters
thread_num	- the number of threads

Returns

void tw::CopyDes2Double ( double *  dst, DTYPE *  src, int  length  )

inline

double tw::DisDes2Double ( double *  dst, DTYPE *  src, int  length  )

inline

template<typename T >

void tw::free_2d	(	T ***	array,
		T *	data
	)

free a continuous 2d array, both the raw pointer to the data and the 2d array pointers are needed.

template void tw::free_2d< double >	(	double ***	array,
		double *	data
	)

template void tw::free_2d< float >	(	float ***	array,
		float *	data
	)

template void tw::free_2d< int >	(	int ***	array,
		int *	data
	)

template void tw::free_2d< vot::LinkEdge >	(	vot::LinkEdge ***	array,
		vot::LinkEdge *	data
	)

void tw::GetIntialCenters	(	size_t	n,
		int	k,
		size_t *	initial_idx
	)

Random sample k indexes for [1...n] without replacement

double tw::Kmeans	(	size_t	num,
		int	dim,
		int	k,
		DTYPE **	p,
		double *	means,
		int *	assignment,
		int	thread_num
	)

void tw::MultiComputeAssignment	(	size_t	num,
		int	dim,
		int	k,
		DTYPE **	des,
		double *	means,
		int *	assignment,
		double *	error_out,
		size_t *	changed_num
	)

void tw::MultiDesAccumulation	(	size_t	num,
		int	dim,
		int	k,
		DTYPE **	p,
		int *	assignment_curr,
		double *	totals,
		size_t *	counts
	)

Accumulate the feature descriptors to the total, a subroutine used by multi-threaded version of ComputeMeans.

Parameters

num	- the total number of feature points
start_id	- the start index for this thread
dim	- the dimension of the feature points
k	- the number of clusters
p	- the address to the starting feature point
assignment_curr	- the current assignments computed by ComputeAssignment
total	- accumulator
counts	- counter

Returns

bool tw::OpencvKeyPoints2libvotSift	(	std::vector< cv::KeyPoint > &	key_points,
		cv::Mat &	descriptors,
		tw::SiftData &	sift_data
	)

int tw::RunVlFeature	(	unsigned char *	data,
		int	image_width,
		int	image_height,
		int	num_channel,
		SiftData &	sift_data,
		VlFeatParam const &	vlfeat_param
	)

bool tw::Vlfeature2LibvotSift	(	std::vector< Vlfeature > const &	vlfeature_vec,
		unsigned char const *	data,
		int	image_width,
		int	image_height,
		int	num_channel,
		tw::SiftData &	sift_data
	)

void tw::VlFeatureDetection	(	unsigned char const *	data,
		std::vector< Vlfeature > &	vlfeature_vec,
		int	image_width,
		int	image_height,
		VlFeatParam const &	vlfeat_param
	)