Class cv::face::FisherFaceRecognizer

#include <opencv2/face/facerec.hpp>

Collaboration diagram for cv::face::FisherFaceRecognizer:

Public Member Functions

Public Member Functions inherited from cv::face::BasicFaceRecognizer

Return	Name	Description
bool	empty()
cv::Mat	getEigenValues()
cv::Mat	getEigenVectors()
cv::Mat	getLabels()
cv::Mat	getMean()
int	getNumComponents()
std::vector< cv::Mat >	getProjections()
double	getThreshold()
void	read(const FileNode & fn)
void	read(const String & filename)	Loads a FaceRecognizer and its model state.
void	setNumComponents(int val)
void	setThreshold(double val)
void	write(const String & filename)	Saves a FaceRecognizer and its model state.
void	write(FileStorage & fs)

Public Member Functions inherited from cv::face::FaceRecognizer

Return	Name	Description
bool	empty()
String	getLabelInfo(int label)	Gets string information by label.
std::vector< int >	getLabelsByString(const String & str)	Gets vector of labels by string.
double	getThreshold()	threshold parameter accessor - required for default BestMinDist collector
int	predict(InputArray src)
void	predict(     InputArray src,     int & label,     double & confidence )	Predicts a label and associated confidence (e.g. distance) for a given input image.
void	predict(     InputArray src,     Ptr< PredictCollector > collector )	if implemented - send all result of prediction to collector that can be used for somehow custom result handling
void	read(const FileNode & fn)
void	read(const String & filename)	Loads a FaceRecognizer and its model state.
void	setLabelInfo(     int label,     const String & strInfo )	Sets string info for the specified model’s label.
void	setThreshold(double val)	Sets threshold of model.
void	train(     InputArrayOfArrays src,     InputArray labels )	Trains a FaceRecognizer with given data and associated labels.
void	update(     InputArrayOfArrays src,     InputArray labels )	Updates a FaceRecognizer with given data and associated labels.
void	write(const String & filename)	Saves a FaceRecognizer and its model state.
void	write(FileStorage & fs)

Public Member Functions inherited from cv::Algorithm

Return	Name	Description
	Algorithm()
	~Algorithm()
void	clear()	Clears the algorithm state.
bool	empty()	Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read.
String	getDefaultName()
void	read(const FileNode & fn)	Reads algorithm parameters from a file storage.
void	save(const String & filename)
void	write(     const Ptr< FileStorage > & fs,     const String & name = String() )
void	write(FileStorage & fs)	Stores algorithm parameters in a file storage.
void	write(     FileStorage & fs,     const String & name )

Static Public Member Functions

Static Public Member Functions inherited from cv::Algorithm

Return	Name	Description
static Ptr< _Tp >	load(     const String & filename,     const String & objname = String() )	Loads algorithm from the file.
static Ptr< _Tp >	loadFromString(     const String & strModel,     const String & objname = String() )	Loads algorithm from a String.
static Ptr< _Tp >	read(const FileNode & fn)	Reads algorithm from the file node.

Additional Inherited Members

Protected Member Functions inherited from cv::Algorithm

Return	Name	Description
void	writeFormat(FileStorage & fs)

Protected Attributes inherited from cv::face::BasicFaceRecognizer

Return	Name	Description
Mat	_eigenvalues
Mat	_eigenvectors
Mat	_labels
Mat	_mean
int	_num_components
std::vector< Mat >	_projections
double	_threshold

Protected Attributes inherited from cv::face::FaceRecognizer

Return	Name	Description
std::map< int, String >	_labelsInfo

Member Function Documentation

create()

static Ptr< FisherFaceRecognizer > cv::face::FisherFaceRecognizer::create(
int num_components = 0,
double threshold = DBL_MAX )

Notes:

• Training and prediction must be done on grayscale images, use cvtColor to convert between the color spaces.

• THE FISHERFACES METHOD MAKES THE ASSUMPTION, THAT THE TRAINING AND TEST IMAGES ARE OF EQUAL SIZE. (caps-lock, because I got so many mails asking for this). You have to make sure your input data has the correct shape, else a meaningful exception is thrown. Use resize to resize the images.

• This model does not support updating.

Model internal data:

• num_components see FisherFaceRecognizer::create.

• threshold see FisherFaceRecognizer::create.

• eigenvalues The eigenvalues for this Linear Discriminant Analysis (ordered descending).

• eigenvectors The eigenvectors for this Linear Discriminant Analysis (ordered by their eigenvalue).

• mean The sample mean calculated from the training data.

• projections The projections of the training data.

• labels The labels corresponding to the projections.

Parameters

• num_components — The number of components (read: Fisherfaces) kept for this Linear Discriminant Analysis with the Fisherfaces criterion. It’s useful to keep all components, that means the number of your classes c (read: subjects, persons you want to recognize). If you leave this at the default (0) or set it to a value less-equal 0 or greater (c-1), it will be set to the correct number (c-1) automatically.

• threshold — The threshold applied in the prediction. If the distance to the nearest neighbor is larger than the threshold, this method returns -1.

Source file

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

• opencv2/face/facerec.hpp