OpenCVForUnity.FaceModule.LBPHFaceRecognizer Class Reference

Public Member Functions
int	getGridX ()
int	getGridY ()
List< Mat >	getHistograms ()
Mat	getLabels ()
int	getNeighbors ()
int	getRadius ()
double	getThreshold ()
void	setGridX (int val)
void	setGridY (int val)
void	setNeighbors (int val)
void	setRadius (int val)
void	setThreshold (double val)
Public Member Functions inherited from OpenCVForUnity.FaceModule.FaceRecognizer
string	getLabelInfo (int label)
	Gets string information by label.
MatOfInt	getLabelsByString (string str)
	Gets vector of labels by string.
void	predict (Mat src, int[] label, double[] confidence)
	Predicts a label and associated confidence (e.g. distance) for a given input image.
void	predict_collect (Mat src, PredictCollector collector)
int	predict_label (Mat src)
void	read (string filename)
	Loads a FaceRecognizer and its model state.
void	setLabelInfo (int label, string strInfo)
	Sets string info for the specified model's label.
void	train (List< Mat > src, Mat labels)
	Trains a FaceRecognizer with given data and associated labels.
void	update (List< Mat > src, Mat labels)
	Updates a FaceRecognizer with given data and associated labels.
void	write (string filename)
	Saves a FaceRecognizer and its model state.
Public Member Functions inherited from OpenCVForUnity.CoreModule.Algorithm
virtual void	clear ()
	Clears the algorithm state.
virtual bool	empty ()
	Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read.
virtual string	getDefaultName ()
IntPtr	getNativeObjAddr ()
void	save (string filename)
Public Member Functions inherited from OpenCVForUnity.DisposableObject
void	Dispose ()
void	ThrowIfDisposed ()

Static Public Member Functions
static new LBPHFaceRecognizer	__fromPtr__ (IntPtr addr)
static LBPHFaceRecognizer	create ()
static LBPHFaceRecognizer	create (int radius)
static LBPHFaceRecognizer	create (int radius, int neighbors)
static LBPHFaceRecognizer	create (int radius, int neighbors, int grid_x)
static LBPHFaceRecognizer	create (int radius, int neighbors, int grid_x, int grid_y)
static LBPHFaceRecognizer	create (int radius, int neighbors, int grid_x, int grid_y, double threshold)
Static Public Member Functions inherited from OpenCVForUnity.FaceModule.FaceRecognizer
static new FaceRecognizer	__fromPtr__ (IntPtr addr)
Static Public Member Functions inherited from OpenCVForUnity.CoreModule.Algorithm
static Algorithm	__fromPtr__ (IntPtr addr)
Static Public Member Functions inherited from OpenCVForUnity.DisposableObject
static IntPtr	ThrowIfNullIntPtr (IntPtr ptr)

Protected Member Functions
override void	Dispose (bool disposing)
Protected Member Functions inherited from OpenCVForUnity.FaceModule.FaceRecognizer
Protected Member Functions inherited from OpenCVForUnity.CoreModule.Algorithm
Protected Member Functions inherited from OpenCVForUnity.DisposableOpenCVObject
	DisposableOpenCVObject ()
	DisposableOpenCVObject (bool isEnabledDispose)
	DisposableOpenCVObject (IntPtr ptr)
	DisposableOpenCVObject (IntPtr ptr, bool isEnabledDispose)
Protected Member Functions inherited from OpenCVForUnity.DisposableObject
	DisposableObject ()
	DisposableObject (bool isEnabledDispose)

Additional Inherited Members
Package Functions inherited from OpenCVForUnity.FaceModule.FaceRecognizer
Package Functions inherited from OpenCVForUnity.CoreModule.Algorithm
Package Attributes inherited from OpenCVForUnity.DisposableOpenCVObject
Properties inherited from OpenCVForUnity.DisposableObject
bool	IsDisposed [get, protected set]
bool	IsEnabledDispose [get, set]

Member Function Documentation

__fromPtr__()

static new LBPHFaceRecognizer OpenCVForUnity.FaceModule.LBPHFaceRecognizer.__fromPtr__ ( IntPtr addr )

static

create() [1/6]

static LBPHFaceRecognizer OpenCVForUnity.FaceModule.LBPHFaceRecognizer.create ( )

static

Parameters

radius	The radius used for building the Circular Local Binary Pattern. The greater the radius, the smoother the image but more spatial information you can get.
neighbors	The number of sample points to build a Circular Local Binary Pattern from. An appropriate value is to use 8 sample points. Keep in mind: the more sample points you include, the higher the computational cost.
grid_x	The number of cells in the horizontal direction, 8 is a common value used in publications. The more cells, the finer the grid, the higher the dimensionality of the resulting feature vector.
grid_y	The number of cells in the vertical direction, 8 is a common value used in publications. The more cells, the finer the grid, the higher the dimensionality of the resulting feature vector.
threshold	The threshold applied in the prediction. If the distance to the nearest neighbor is larger than the threshold, this method returns -1.

Notes:

• The Circular Local Binary Patterns (used in training and prediction) expect the data given as grayscale images, use cvtColor to convert between the color spaces.
• This model supports updating.

Model internal data:

• radius see LBPHFaceRecognizer.create.
• neighbors see LBPHFaceRecognizer.create.
• grid_x see LLBPHFaceRecognizer::create.
• grid_y see LBPHFaceRecognizer.create.
• threshold see LBPHFaceRecognizer.create.
• histograms Local Binary Patterns Histograms calculated from the given training data (empty if none was given).
• labels Labels corresponding to the calculated Local Binary Patterns Histograms.

create() [2/6]

static LBPHFaceRecognizer OpenCVForUnity.FaceModule.LBPHFaceRecognizer.create ( int radius )

static

Parameters

radius	The radius used for building the Circular Local Binary Pattern. The greater the radius, the smoother the image but more spatial information you can get.
neighbors	The number of sample points to build a Circular Local Binary Pattern from. An appropriate value is to use 8 sample points. Keep in mind: the more sample points you include, the higher the computational cost.
grid_x	The number of cells in the horizontal direction, 8 is a common value used in publications. The more cells, the finer the grid, the higher the dimensionality of the resulting feature vector.
grid_y	The number of cells in the vertical direction, 8 is a common value used in publications. The more cells, the finer the grid, the higher the dimensionality of the resulting feature vector.
threshold	The threshold applied in the prediction. If the distance to the nearest neighbor is larger than the threshold, this method returns -1.

Notes:

• The Circular Local Binary Patterns (used in training and prediction) expect the data given as grayscale images, use cvtColor to convert between the color spaces.
• This model supports updating.

Model internal data:

• radius see LBPHFaceRecognizer.create.
• neighbors see LBPHFaceRecognizer.create.
• grid_x see LLBPHFaceRecognizer::create.
• grid_y see LBPHFaceRecognizer.create.
• threshold see LBPHFaceRecognizer.create.
• histograms Local Binary Patterns Histograms calculated from the given training data (empty if none was given).
• labels Labels corresponding to the calculated Local Binary Patterns Histograms.

create() [3/6]

static LBPHFaceRecognizer OpenCVForUnity.FaceModule.LBPHFaceRecognizer.create ( int radius, int neighbors )

static

Parameters

radius	The radius used for building the Circular Local Binary Pattern. The greater the radius, the smoother the image but more spatial information you can get.
neighbors	The number of sample points to build a Circular Local Binary Pattern from. An appropriate value is to use 8 sample points. Keep in mind: the more sample points you include, the higher the computational cost.
grid_x	The number of cells in the horizontal direction, 8 is a common value used in publications. The more cells, the finer the grid, the higher the dimensionality of the resulting feature vector.
grid_y	The number of cells in the vertical direction, 8 is a common value used in publications. The more cells, the finer the grid, the higher the dimensionality of the resulting feature vector.
threshold	The threshold applied in the prediction. If the distance to the nearest neighbor is larger than the threshold, this method returns -1.

Notes:

• The Circular Local Binary Patterns (used in training and prediction) expect the data given as grayscale images, use cvtColor to convert between the color spaces.
• This model supports updating.

Model internal data:

• radius see LBPHFaceRecognizer.create.
• neighbors see LBPHFaceRecognizer.create.
• grid_x see LLBPHFaceRecognizer::create.
• grid_y see LBPHFaceRecognizer.create.
• threshold see LBPHFaceRecognizer.create.
• histograms Local Binary Patterns Histograms calculated from the given training data (empty if none was given).
• labels Labels corresponding to the calculated Local Binary Patterns Histograms.

create() [4/6]

static LBPHFaceRecognizer OpenCVForUnity.FaceModule.LBPHFaceRecognizer.create ( int radius, int neighbors, int grid_x )

static

Parameters

radius	The radius used for building the Circular Local Binary Pattern. The greater the radius, the smoother the image but more spatial information you can get.
neighbors	The number of sample points to build a Circular Local Binary Pattern from. An appropriate value is to use 8 sample points. Keep in mind: the more sample points you include, the higher the computational cost.
grid_x	The number of cells in the horizontal direction, 8 is a common value used in publications. The more cells, the finer the grid, the higher the dimensionality of the resulting feature vector.
grid_y	The number of cells in the vertical direction, 8 is a common value used in publications. The more cells, the finer the grid, the higher the dimensionality of the resulting feature vector.
threshold	The threshold applied in the prediction. If the distance to the nearest neighbor is larger than the threshold, this method returns -1.

Notes:

• The Circular Local Binary Patterns (used in training and prediction) expect the data given as grayscale images, use cvtColor to convert between the color spaces.
• This model supports updating.

Model internal data:

• radius see LBPHFaceRecognizer.create.
• neighbors see LBPHFaceRecognizer.create.
• grid_x see LLBPHFaceRecognizer::create.
• grid_y see LBPHFaceRecognizer.create.
• threshold see LBPHFaceRecognizer.create.
• histograms Local Binary Patterns Histograms calculated from the given training data (empty if none was given).
• labels Labels corresponding to the calculated Local Binary Patterns Histograms.

create() [5/6]

static LBPHFaceRecognizer OpenCVForUnity.FaceModule.LBPHFaceRecognizer.create ( int radius, int neighbors, int grid_x, int grid_y )

static

Parameters

radius	The radius used for building the Circular Local Binary Pattern. The greater the radius, the smoother the image but more spatial information you can get.
neighbors	The number of sample points to build a Circular Local Binary Pattern from. An appropriate value is to use 8 sample points. Keep in mind: the more sample points you include, the higher the computational cost.
grid_x	The number of cells in the horizontal direction, 8 is a common value used in publications. The more cells, the finer the grid, the higher the dimensionality of the resulting feature vector.
grid_y	The number of cells in the vertical direction, 8 is a common value used in publications. The more cells, the finer the grid, the higher the dimensionality of the resulting feature vector.
threshold	The threshold applied in the prediction. If the distance to the nearest neighbor is larger than the threshold, this method returns -1.

Notes:

• The Circular Local Binary Patterns (used in training and prediction) expect the data given as grayscale images, use cvtColor to convert between the color spaces.
• This model supports updating.

Model internal data:

• radius see LBPHFaceRecognizer.create.
• neighbors see LBPHFaceRecognizer.create.
• grid_x see LLBPHFaceRecognizer::create.
• grid_y see LBPHFaceRecognizer.create.
• threshold see LBPHFaceRecognizer.create.
• histograms Local Binary Patterns Histograms calculated from the given training data (empty if none was given).
• labels Labels corresponding to the calculated Local Binary Patterns Histograms.

create() [6/6]

static LBPHFaceRecognizer OpenCVForUnity.FaceModule.LBPHFaceRecognizer.create ( int radius, int neighbors, int grid_x, int grid_y, double threshold )

static

Parameters

radius	The radius used for building the Circular Local Binary Pattern. The greater the radius, the smoother the image but more spatial information you can get.
neighbors	The number of sample points to build a Circular Local Binary Pattern from. An appropriate value is to use 8 sample points. Keep in mind: the more sample points you include, the higher the computational cost.
grid_x	The number of cells in the horizontal direction, 8 is a common value used in publications. The more cells, the finer the grid, the higher the dimensionality of the resulting feature vector.
grid_y	The number of cells in the vertical direction, 8 is a common value used in publications. The more cells, the finer the grid, the higher the dimensionality of the resulting feature vector.
threshold	The threshold applied in the prediction. If the distance to the nearest neighbor is larger than the threshold, this method returns -1.

Notes:

• The Circular Local Binary Patterns (used in training and prediction) expect the data given as grayscale images, use cvtColor to convert between the color spaces.
• This model supports updating.

Model internal data:

• radius see LBPHFaceRecognizer.create.
• neighbors see LBPHFaceRecognizer.create.
• grid_x see LLBPHFaceRecognizer::create.
• grid_y see LBPHFaceRecognizer.create.
• threshold see LBPHFaceRecognizer.create.
• histograms Local Binary Patterns Histograms calculated from the given training data (empty if none was given).
• labels Labels corresponding to the calculated Local Binary Patterns Histograms.

Dispose()

override void OpenCVForUnity.FaceModule.LBPHFaceRecognizer.Dispose ( bool disposing )

protectedvirtual

Reimplemented from OpenCVForUnity.FaceModule.FaceRecognizer.

getGridX()

int OpenCVForUnity.FaceModule.LBPHFaceRecognizer.getGridX

(

)

See also

setGridX

getGridY()

int OpenCVForUnity.FaceModule.LBPHFaceRecognizer.getGridY

(

)

See also

setGridY

getHistograms()

List< Mat > OpenCVForUnity.FaceModule.LBPHFaceRecognizer.getHistograms

(

)

getLabels()

Mat OpenCVForUnity.FaceModule.LBPHFaceRecognizer.getLabels

(

)

getNeighbors()

int OpenCVForUnity.FaceModule.LBPHFaceRecognizer.getNeighbors

(

)

See also

setNeighbors

getRadius()

int OpenCVForUnity.FaceModule.LBPHFaceRecognizer.getRadius

(

)

See also

setRadius

getThreshold()

double OpenCVForUnity.FaceModule.LBPHFaceRecognizer.getThreshold

(

)

See also

setThreshold

setGridX()

void OpenCVForUnity.FaceModule.LBPHFaceRecognizer.setGridX

(

int

val

)

See also

getGridX

setGridY()

void OpenCVForUnity.FaceModule.LBPHFaceRecognizer.setGridY

(

int

val

)

See also

getGridY

setNeighbors()

void OpenCVForUnity.FaceModule.LBPHFaceRecognizer.setNeighbors

(

int

val

)

See also

getNeighbors

setRadius()

void OpenCVForUnity.FaceModule.LBPHFaceRecognizer.setRadius

(

int

val

)

See also

getRadius

setThreshold()

void OpenCVForUnity.FaceModule.LBPHFaceRecognizer.setThreshold

(

double

val

)

See also

getThreshold

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

• OpenCVForUnity/Assets/OpenCVForUnity/org/opencv_contrib/face/LBPHFaceRecognizer.cs