#include <ml.hpp>

Inheritance diagram for cv::EM:

Public Types
enum	{ COV_MAT_SPHERICAL =0, COV_MAT_DIAGONAL =1, COV_MAT_GENERIC =2, COV_MAT_DEFAULT =COV_MAT_DIAGONAL }

enum	{ DEFAULT_NCLUSTERS =5, DEFAULT_MAX_ITERS =100 }

enum	{ START_E_STEP =1, START_M_STEP =2, START_AUTO_STEP =0 }

Public Types inherited from cv::Algorithm
typedef Algorithm (	Constructor) (void)

typedef int(Algorithm::*	Getter) () const

typedef void(Algorithm::*	Setter) (int)

Public Member Functions
	EM (int nclusters=EM::DEFAULT_NCLUSTERS, int covMatType=EM::COV_MAT_DIAGONAL, const TermCriteria &termCrit=TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, EM::DEFAULT_MAX_ITERS, FLT_EPSILON))

virtual	~EM ()

virtual void	clear ()

virtual bool	train (InputArray samples, OutputArray logLikelihoods=noArray(), OutputArray labels=noArray(), OutputArray probs=noArray())

virtual bool	trainE (InputArray samples, InputArray means0, InputArray covs0=noArray(), InputArray weights0=noArray(), OutputArray logLikelihoods=noArray(), OutputArray labels=noArray(), OutputArray probs=noArray())

virtual bool	trainM (InputArray samples, InputArray probs0, OutputArray logLikelihoods=noArray(), OutputArray labels=noArray(), OutputArray probs=noArray())

Vec2d	predict (InputArray sample, OutputArray probs=noArray()) const

bool	isTrained () const

AlgorithmInfo *	info () const

virtual void	read (const FileNode &fn)

Public Member Functions inherited from cv::Algorithm
	Algorithm ()

virtual	~Algorithm ()

string	name () const

template<typename _Tp >
ParamType< _Tp >::member_type	get (const string &name) const

template<typename _Tp >
ParamType< _Tp >::member_type	get (const char *name) const

int	getInt (const string &name) const

double	getDouble (const string &name) const

bool	getBool (const string &name) const

string	getString (const string &name) const

Mat	getMat (const string &name) const

vector< Mat >	getMatVector (const string &name) const

Ptr< Algorithm >	getAlgorithm (const string &name) const

void	set (const string &name, int value)

void	set (const string &name, double value)

void	set (const string &name, bool value)

void	set (const string &name, const string &value)

void	set (const string &name, const Mat &value)

void	set (const string &name, const vector< Mat > &value)

void	set (const string &name, const Ptr< Algorithm > &value)

template<typename _Tp >
void	set (const string &name, const Ptr< _Tp > &value)

void	setInt (const string &name, int value)

void	setDouble (const string &name, double value)

void	setBool (const string &name, bool value)

void	setString (const string &name, const string &value)

void	setMat (const string &name, const Mat &value)

void	setMatVector (const string &name, const vector< Mat > &value)

void	setAlgorithm (const string &name, const Ptr< Algorithm > &value)

template<typename _Tp >
void	setAlgorithm (const string &name, const Ptr< _Tp > &value)

void	set (const char *name, int value)

void	set (const char *name, double value)

void	set (const char *name, bool value)

void	set (const char *name, const string &value)

void	set (const char *name, const Mat &value)

void	set (const char *name, const vector< Mat > &value)

void	set (const char *name, const Ptr< Algorithm > &value)

template<typename _Tp >
void	set (const char *name, const Ptr< _Tp > &value)

void	setInt (const char *name, int value)

void	setDouble (const char *name, double value)

void	setBool (const char *name, bool value)

void	setString (const char *name, const string &value)

void	setMat (const char *name, const Mat &value)

void	setMatVector (const char *name, const vector< Mat > &value)

void	setAlgorithm (const char *name, const Ptr< Algorithm > &value)

template<typename _Tp >
void	setAlgorithm (const char *name, const Ptr< _Tp > &value)

string	paramHelp (const string &name) const

int	paramType (const char *name) const

int	paramType (const string &name) const

void	getParams (CV_OUT vector< string > &names) const

virtual void	write (FileStorage &fs) const

Protected Member Functions
virtual void	setTrainData (int startStep, const Mat &samples, const Mat probs0, const Mat means0, const vector< Mat > covs0, const Mat weights0)

bool	doTrain (int startStep, OutputArray logLikelihoods, OutputArray labels, OutputArray probs)

virtual void	eStep ()

virtual void	mStep ()

void	clusterTrainSamples ()

void	decomposeCovs ()

void	computeLogWeightDivDet ()

Vec2d	computeProbabilities (const Mat &sample, Mat *probs) const

Protected Attributes
int	nclusters

int	covMatType

int	maxIters

double	epsilon

Mat	trainSamples

Mat	trainProbs

Mat	trainLogLikelihoods

Mat	trainLabels

CV_PROP Mat	weights

CV_PROP Mat	means

CV_PROP vector< Mat >	covs

vector< Mat >	covsEigenValues

vector< Mat >	covsRotateMats

vector< Mat >	invCovsEigenValues

Mat	logWeightDivDet

Additional Inherited Members
Static Public Member Functions inherited from cv::Algorithm
static void	getList (CV_OUT vector< string > &algorithms)

static Ptr< Algorithm >	_create (const string &name)

template<typename _Tp >
static Ptr< _Tp >	create (const string &name)

Member Enumeration Documentation

§ anonymous enum

anonymous enum

Enumerator
COV_MAT_SPHERICAL
COV_MAT_DIAGONAL
COV_MAT_GENERIC
COV_MAT_DEFAULT

§ anonymous enum

anonymous enum

Enumerator
DEFAULT_NCLUSTERS
DEFAULT_MAX_ITERS

§ anonymous enum

anonymous enum

Enumerator
START_E_STEP
START_M_STEP
START_AUTO_STEP

Constructor & Destructor Documentation

§ EM()

cv::EM::EM	(	int	nclusters = `EM::DEFAULT_NCLUSTERS`,
		int	covMatType = `EM::COV_MAT_DIAGONAL`,
		const TermCriteria &	termCrit = `TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, EM::DEFAULT_MAX_ITERS, FLT_EPSILON)`
	)

§ ~EM()

virtual cv::EM::~EM ( )

virtual

Member Function Documentation

§ clear()

virtual void cv::EM::clear ( )

virtual

§ clusterTrainSamples()

void cv::EM::clusterTrainSamples ( )

protected

§ computeLogWeightDivDet()

void cv::EM::computeLogWeightDivDet ( )

protected

§ computeProbabilities()

Vec2d cv::EM::computeProbabilities	(	const Mat &	sample,
		Mat *	probs
	)		const

protected

§ decomposeCovs()

void cv::EM::decomposeCovs ( )

protected

§ doTrain()

bool cv::EM::doTrain	(	int	startStep,
		OutputArray	logLikelihoods,
		OutputArray	labels,
		OutputArray	probs
	)

protected

§ eStep()

virtual void cv::EM::eStep ( )

protectedvirtual

§ info()

AlgorithmInfo* cv::EM::info ( ) const

virtual

Reimplemented from cv::Algorithm.

§ isTrained()

bool cv::EM::isTrained ( ) const

§ mStep()

virtual void cv::EM::mStep ( )

protectedvirtual

§ predict()

Vec2d cv::EM::predict	(	InputArray	sample,
		OutputArray	probs = `noArray()`
	)		const

§ read()

virtual void cv::EM::read ( const FileNode & fn )

virtual

Reimplemented from cv::Algorithm.

§ setTrainData()

virtual void cv::EM::setTrainData	(	int	startStep,
		const Mat &	samples,
		const Mat *	probs0,
		const Mat *	means0,
		const vector< Mat > *	covs0,
		const Mat *	weights0
	)

protectedvirtual

§ train()

virtual bool cv::EM::train	(	InputArray	samples,
		OutputArray	logLikelihoods = `noArray()`,
		OutputArray	labels = `noArray()`,
		OutputArray	probs = `noArray()`
	)

virtual

§ trainE()

virtual bool cv::EM::trainE	(	InputArray	samples,
		InputArray	means0,
		InputArray	covs0 = `noArray()`,
		InputArray	weights0 = `noArray()`,
		OutputArray	logLikelihoods = `noArray()`,
		OutputArray	labels = `noArray()`,
		OutputArray	probs = `noArray()`
	)

virtual

§ trainM()

virtual bool cv::EM::trainM	(	InputArray	samples,
		InputArray	probs0,
		OutputArray	logLikelihoods = `noArray()`,
		OutputArray	labels = `noArray()`,
		OutputArray	probs = `noArray()`
	)

virtual

Member Data Documentation

§ covMatType

int cv::EM::covMatType

protected

§ covs

CV_PROP vector<Mat> cv::EM::covs

protected

§ covsEigenValues

vector<Mat> cv::EM::covsEigenValues

protected

§ covsRotateMats

vector<Mat> cv::EM::covsRotateMats

protected

§ epsilon

double cv::EM::epsilon

protected

§ invCovsEigenValues

vector<Mat> cv::EM::invCovsEigenValues

protected

§ logWeightDivDet

Mat cv::EM::logWeightDivDet

protected

§ maxIters

int cv::EM::maxIters

protected

§ means

CV_PROP Mat cv::EM::means

protected

§ nclusters

int cv::EM::nclusters

protected

§ trainLabels

Mat cv::EM::trainLabels

protected

§ trainLogLikelihoods

Mat cv::EM::trainLogLikelihoods

protected

§ trainProbs

Mat cv::EM::trainProbs

protected

§ trainSamples

Mat cv::EM::trainSamples

protected

§ weights

CV_PROP Mat cv::EM::weights

protected

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

ml/ml.hpp

Public Types

Public Member Functions

Protected Member Functions

Protected Attributes

Additional Inherited Members

Member Enumeration Documentation

§ anonymous enum

§ anonymous enum

§ anonymous enum

Constructor & Destructor Documentation

§ EM()

§ ~EM()

Member Function Documentation

§ clear()

§ clusterTrainSamples()

§ computeLogWeightDivDet()

§ computeProbabilities()

§ decomposeCovs()

§ doTrain()

§ eStep()

§ info()

§ isTrained()

§ mStep()

§ predict()

§ read()

§ setTrainData()

§ train()

§ trainE()

§ trainM()

Member Data Documentation

§ covMatType

§ covs

§ covsEigenValues

§ covsRotateMats

§ epsilon

§ invCovsEigenValues

§ logWeightDivDet

§ maxIters

§ means

§ nclusters

§ trainLabels

§ trainLogLikelihoods

§ trainProbs

§ trainSamples

§ weights