OpenCV Gaussian Mixture Model training class. More...

#include <TrainNodeCvGMM.h>

Inheritance diagram for DirectGraphicalModels::CTrainNodeCvGMM:

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Collaboration diagram for DirectGraphicalModels::CTrainNodeCvGMM:

Public Member Functions
	CTrainNodeCvGMM (byte nStates, word nFeatures, TrainNodeCvGMMParams params=TRAIN_NODE_CV_GMM_PARAMS_DEFAULT)
	Constructor. More...

	CTrainNodeCvGMM (byte nStates, word nFeatures, int maxSamples, byte nGausses=TRAIN_NODE_CV_GMM_PARAMS_DEFAULT.numGausses)
	Constructor. More...

virtual	~CTrainNodeCvGMM (void)

void	reset (void)
	Resets class variables. More...

void	save (const std::string &path, const std::string &name=std::string(), short idx=-1) const
	Saves the training data. More...

void	load (const std::string &path, const std::string &name=std::string(), short idx=-1)
	Loads the training data. More...

void	addFeatureVec (const Mat &featureVector, byte gt)
	Adds new feature vector. More...

void	train (bool doClean=false)
	Random model training. More...

Public Member Functions inherited from DirectGraphicalModels::CTrainNode
	CTrainNode (byte nStates, word nFeatures)
	Constructor. More...

virtual	~CTrainNode (void)

void	addFeatureVec (const Mat &featureVectors, const Mat &gt)
	Adds a block of new feature vectors. More...

void	addFeatureVec (const vec_mat_t &featureVectors, const Mat &gt)
	Adds a block of new feature vectors. More...

Mat	getNodePotentials (const Mat &featureVector, float weight=1.0f) const
	Returns the node potential, based on the feature vector. More...

Public Member Functions inherited from DirectGraphicalModels::ITrain
	ITrain (byte nStates, word nFeatures)
	Constructor. More...

virtual	~ITrain (void)

word	getNumFeatures (void) const
	Returns number of features. More...

Public Member Functions inherited from DirectGraphicalModels::CBaseRandomModel
	CBaseRandomModel (byte nStates)
	Constructor. More...

virtual	~CBaseRandomModel (void)

byte	getNumStates (void) const
	Returns number of features. More...

Protected Member Functions
void	saveFile (FILE *pFile) const
	Saves the random model into the file. More...

void	loadFile (FILE *pFile)
	Loads the random model from the file. More...

void	calculateNodePotentials (const Mat &featureVector, Mat &potential, Mat &mask) const
	Calculates the node potential, based on the feature vector. More...

Protected Member Functions inherited from DirectGraphicalModels::CBaseRandomModel
std::string	generateFileName (const std::string &path, const std::string &name, short idx) const
	Generates name of the data file for storing random model parameters. More...

Additional Inherited Members
Protected Attributes inherited from DirectGraphicalModels::ITrain
word	m_nFeatures
	The number of features (length of the feature vector) More...

Protected Attributes inherited from DirectGraphicalModels::CBaseRandomModel
byte	m_nStates
	The number of states (classes) More...

Detailed Description

OpenCV Gaussian Mixture Model training class.

Author: Sergey G. Kosov, serge.nosp@m.y.ko.nosp@m.sov@p.nosp@m.roje.nosp@m.ct-10.nosp@m..de

Definition at line 37 of file TrainNodeCvGMM.h.

Constructor & Destructor Documentation

DirectGraphicalModels::CTrainNodeCvGMM::CTrainNodeCvGMM	(	byte	nStates,
		word	nFeatures,
		TrainNodeCvGMMParams	params = `TRAIN_NODE_CV_GMM_PARAMS_DEFAULT`
	)

Constructor.

Parameters

nStates	Number of states (classes)
nFeatures	Number of features
params	Expectation Maximization parameters (Ref. TrainNodeCvGMMParams)

Definition at line 11 of file TrainNodeCvGMM.cpp.

DirectGraphicalModels::CTrainNodeCvGMM::CTrainNodeCvGMM	(	byte	nStates,
		word	nFeatures,
		int	maxSamples,
		byte	nGausses = `TRAIN_NODE_CV_GMM_PARAMS_DEFAULT.numGausses`
	)

Constructor.

Parameters

nStates	Number of states (classes)
nFeatures	Number of features
maxSamples	Maximum number of samples to be used in training
nGausses	The number of mixture components in the Gaussian Mixture Model per state (class)

Definition at line 17 of file TrainNodeCvGMM.cpp.

DirectGraphicalModels::CTrainNodeCvGMM::~CTrainNodeCvGMM ( void )

virtual

Definition at line 42 of file TrainNodeCvGMM.cpp.

Member Function Documentation

void DirectGraphicalModels::CTrainNodeCvGMM::addFeatureVec	(	const Mat &	featureVector,
		byte	gt
	)

virtual

Adds new feature vector.

Used to add a featureVector, corresponding to the ground-truth state (class) gt for training

Parameters

featureVector	Multi-dimensinal point: Mat(size: nFeatures x 1; type: CV_8UC1)
gt	Corresponding ground-truth state (class)

Implements DirectGraphicalModels::CTrainNode.

Definition at line 76 of file TrainNodeCvGMM.cpp.

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void DirectGraphicalModels::CTrainNodeCvGMM::calculateNodePotentials	(	const Mat &	featureVector,
		Mat &	potential,
		Mat &	mask
	)		const

protectedvirtual

Calculates the node potential, based on the feature vector.

This function calculates the potentials of the node, described with the sample featureVector, being in each state (belonging to each class). These potentials are united in the node potential vector:

\[nodePot[nStates] = f(\textbf{f}[nFeatures]).\]

Functions \( f \) must be implemented in derived classes.

Parameters

[in]	featureVector	Multi-dimensinal point \(\textbf{f}\): Mat(size: nFeatures x 1; type: CV_{XX}C1)
[in,out]	potential	Node potentials: Mat(size: nStates x 1; type: CV_32FC1). This parameter should be preinitialized and set to value 0.
[in,out]	mask	Relevant Node potentials: Mat(size: nStates x 1; type: CV_8UC1). This parameter should be preinitialized and set to value 1 (all potentials are relevant).

Implements DirectGraphicalModels::CTrainNode.

Definition at line 112 of file TrainNodeCvGMM.cpp.

void DirectGraphicalModels::CTrainNodeCvGMM::load	(	const std::string &	path,
		const std::string &	name = `std::string()`,
		short	idx = `-1`
	)

virtual

Loads the training data.

Allows to re-use the class. Loads data to the file: "<path><name>_<idx>.dat".

Parameters

path	Path to the folder, containing the data file.
name	Name of data file. If empty, will be generated automatically from the class name.
idx	Index of the data file. Negative value means no index.

Reimplemented from DirectGraphicalModels::CBaseRandomModel.

Definition at line 62 of file TrainNodeCvGMM.cpp.

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void DirectGraphicalModels::CTrainNodeCvGMM::loadFile ( FILE * pFile )

inlineprotectedvirtual

Loads the random model from the file.

Allows to re-use the class.

Parameters

pFile Pointer to the file, opened for reading.

Implements DirectGraphicalModels::CBaseRandomModel.

Definition at line 68 of file TrainNodeCvGMM.h.

void DirectGraphicalModels::CTrainNodeCvGMM::reset ( void )

virtual

Resets class variables.

Allows to re-use the class.

Implements DirectGraphicalModels::CBaseRandomModel.

Definition at line 47 of file TrainNodeCvGMM.cpp.

void DirectGraphicalModels::CTrainNodeCvGMM::save	(	const std::string &	path,
		const std::string &	name = `std::string()`,
		short	idx = `-1`
	)		const

virtual

Saves the training data.

Allows to re-use the class. Stores data to the file: "<path><name>_<idx>.dat".

Parameters

path	Path to the destination folder.
name	Name of data file. If empty, will be generated automatically from the class name.
idx	Index of the destination file. Negative value means no index.

Reimplemented from DirectGraphicalModels::CBaseRandomModel.

Definition at line 54 of file TrainNodeCvGMM.cpp.

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void DirectGraphicalModels::CTrainNodeCvGMM::saveFile ( FILE * pFile ) const

inlineprotectedvirtual

Saves the random model into the file.

Allows to re-use the class.

Parameters

pFile Pointer to the file, opened for writing.

Implements DirectGraphicalModels::CBaseRandomModel.

Definition at line 67 of file TrainNodeCvGMM.h.

void DirectGraphicalModels::CTrainNodeCvGMM::train ( bool doClean = false )

virtual

Random model training.

Auxilary function for training - some derived classes may use this function inbetween training and classification phases

Note: This function must be called inbetween the training and classification phases

Parameters

doClean Flag indicating if the memory, keeping the trining data should be released after training

Reimplemented from DirectGraphicalModels::CTrainNode.

Definition at line 92 of file TrainNodeCvGMM.cpp.

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

D:/Projects/DGM/modules/DGM/TrainNodeCvGMM.h
D:/Projects/DGM/modules/DGM/TrainNodeCvGMM.cpp

Public Member Functions

Protected Member Functions

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

Member Function Documentation