DirectGraphicalModels::CTrainNodeGM Class Reference

Gaussian Model training class. More...

#include <TrainNodeGM.h>

Inheritance diagram for DirectGraphicalModels::CTrainNodeGM:

Collaboration diagram for DirectGraphicalModels::CTrainNodeGM:

Public Member Functions
	CTrainNodeGM (byte nStates, word nFeatures)
	Constructor. More...
	~CTrainNodeGM (void)
Mat	getNodePotentials (const Mat &featureVector, float weight=1.0f)
	Returns the node potential, based on the feature vector. More...
Public Member Functions inherited from DirectGraphicalModels::CTrainNodeGMM
	CTrainNodeGMM (byte nStates, word nFeatures, TrainNodeGMMParams params=TRAIN_NODE_GMM_PARAMS_DEFAULT)
	Constructor. More...
	CTrainNodeGMM (byte nStates, word nFeatures, byte maxGausses)
	Constructor. More...
virtual	~CTrainNodeGMM (void)
void	reset (void)
	Resets class variables. 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)=default
void	addFeatureVecs (const Mat &featureVectors, const Mat &gt)
	Adds a block of new feature vectors. More...
void	addFeatureVecs (const vec_mat_t &featureVectors, const Mat &gt)
	Adds a block of new feature vectors. More...
Mat	getNodePotentials (const Mat &featureVectors, const Mat &weights=Mat(), float Z=0.0f) const
	Returns a block of node potentials, based on the block of feature vector. More...
Mat	getNodePotentials (const vec_mat_t &featureVectors, const Mat &weights=Mat(), float Z=0.0f) const
	Returns a block of node potentials, based on the block of feature vector. More...
Mat	getNodePotentials (const Mat &featureVector, float weight, float Z=0.0f) 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)=default
word	getNumFeatures (void) const
	Returns number of features. More...
Public Member Functions inherited from DirectGraphicalModels::CBaseRandomModel
	CBaseRandomModel (byte nStates)
	Constructor. More...
virtual	~CBaseRandomModel (void)
virtual void	save (const std::string &path, const std::string &name=std::string(), short idx=-1) const
	Saves the training data. More...
virtual void	load (const std::string &path, const std::string &name=std::string(), short idx=-1)
	Loads the training data. More...
byte	getNumStates (void) const
	Returns number of states (classes) More...

Additional Inherited Members
Static Public Member Functions inherited from DirectGraphicalModels::CTrainNode
static std::shared_ptr< CTrainNode >	create (byte nodeRandomModel, byte nStates, word nFeatures)
	Factory method returning node trainer object. More...
Protected Member Functions inherited from DirectGraphicalModels::CTrainNodeGMM
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...
Protected Attributes inherited from DirectGraphicalModels::CBaseRandomModel
byte	m_nStates
	The number of states (classes) More...

Detailed Description

Gaussian Model training class.

This class realizes the generative training mechanism, based on the idea of approximating a the density of multi-dimensional random variables with a single multi-dimensional Gaussian function.

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 18 of file TrainNodeGM.h.

Constructor & Destructor Documentation

CTrainNodeGM()

DirectGraphicalModels::CTrainNodeGM::CTrainNodeGM ( byte  nStates, word  nFeatures  )

inline

Constructor.

Parameters

nStates	Number of states (classes)
nFeatures	Number of features

Definition at line 26 of file TrainNodeGM.h.

~CTrainNodeGM()

DirectGraphicalModels::CTrainNodeGM::~CTrainNodeGM ( void  )

inline

Definition at line 27 of file TrainNodeGM.h.

Member Function Documentation

getNodePotentials()

Mat DirectGraphicalModels::CTrainNodeGM::getNodePotentials ( const Mat &  featureVector, float  weight = 1.0f  )

inline

Returns the node potential, based on the feature vector.

This function calculates the potentials of the node, described with the sample featureVector ( \( \textbf{f} \)): \( nodePot_s = \mathcal{N}_s(\textbf{f}), \forall s \in \mathbb{S} \), where \(\mathbb{S}\) is the set of all states (classes). In other words, the indexes: \( s \in [0; nStates) \). Here \( \mathcal{N} \) is a Gaussian function kernel, described in class CKDGauss

Parameters

featureVector	Multi-dimensinal point \(\textbf{f}\): Mat(size: nFeatures x 1; type: CV_{XX}C1)
weight	The weighting parameter

Returns

Node potentials on success: Mat(size: nStates x 1; type: CV_32FC1); empty Mat() otherwise

Definition at line 38 of file TrainNodeGM.h.

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

• D:/Projects/DGM/modules/DGM/TrainNodeGM.h