cv::face::FisherFaceRecognizer Class Reference

#include <opencv2/face/facerec.hpp>

Static Public Member Functions
static Ptr< FisherFaceRecognizer >	create (int num_components=0, double threshold=DBL_MAX)
Static Public Member Functions inherited from cv::Algorithm
template<typename _Tp>
static Ptr< _Tp >	load (const String &filename, const String &objname=String())
	Loads algorithm from the file.
template<typename _Tp>
static Ptr< _Tp >	loadFromString (const String &strModel, const String &objname=String())
	Loads algorithm from a String.
template<typename _Tp>
static Ptr< _Tp >	read (const FileNode &fn)
	Reads algorithm from the file node.

Additional Inherited Members
Public Member Functions inherited from cv::face::BasicFaceRecognizer
virtual bool	empty () const CV_OVERRIDE
cv::Mat	getEigenValues () const
cv::Mat	getEigenVectors () const
cv::Mat	getLabels () const
cv::Mat	getMean () const
int	getNumComponents () const
std::vector< cv::Mat >	getProjections () const
double	getThreshold () const CV_OVERRIDE
virtual void	read (const FileNode &fn) CV_OVERRIDE
virtual void	read (const String &filename)
	Loads a FaceRecognizer and its model state.
void	setNumComponents (int val)
void	setThreshold (double val) CV_OVERRIDE
virtual void	write (const String &filename) const
	Saves a FaceRecognizer and its model state.
virtual void	write (FileStorage &fs) const CV_OVERRIDE
Public Member Functions inherited from cv::face::FaceRecognizer
virtual String	getLabelInfo (int label) const
	Gets string information by label.
virtual std::vector< int >	getLabelsByString (const String &str) const
	Gets vector of labels by string.
int	predict (InputArray src) const
void	predict (InputArray src, int &label, double &confidence) const
	Predicts a label and associated confidence (e.g. distance) for a given input image.
virtual void	predict (InputArray src, Ptr< PredictCollector > collector) const =0
	if implemented - send all result of prediction to collector that can be used for somehow custom result handling
virtual void	setLabelInfo (int label, const String &strInfo)
	Sets string info for the specified model's label.
virtual void	train (InputArrayOfArrays src, InputArray labels)=0
	Trains a FaceRecognizer with given data and associated labels.
virtual void	update (InputArrayOfArrays src, InputArray labels)
	Updates a FaceRecognizer with given data and associated labels.
Public Member Functions inherited from cv::Algorithm
	Algorithm ()
virtual	~Algorithm ()
virtual void	clear ()
	Clears the algorithm state.
virtual String	getDefaultName () const
virtual void	save (const String &filename) const
void	write (const Ptr< FileStorage > &fs, const String &name=String()) const
void	write (FileStorage &fs, const String &name) const
Protected Member Functions inherited from cv::Algorithm
void	writeFormat (FileStorage &fs) const
Protected Attributes inherited from cv::face::BasicFaceRecognizer
Mat	_eigenvalues
Mat	_eigenvectors
Mat	_labels
Mat	_mean
int	_num_components
std::vector< Mat >	_projections
double	_threshold
Protected Attributes inherited from cv::face::FaceRecognizer
std::map< int, String >	_labelsInfo

Member Function Documentation

create()

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

static

Python:
	cv.face.FisherFaceRecognizer.create(	[, num_components[, threshold]]	) ->	retval
	cv.face.FisherFaceRecognizer_create(	[, num_components[, threshold]]	) ->	retval

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.

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.

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

• opencv2/face/facerec.hpp