
static new LBPHFaceRecognizer  __fromPtr__ (IntPtr addr) 

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

static LBPHFaceRecognizer  create (int radius, int neighbors, int grid_x, int grid_y) 

static LBPHFaceRecognizer  create (int radius, int neighbors, int grid_x) 

static LBPHFaceRecognizer  create (int radius, int neighbors) 

static LBPHFaceRecognizer  create (int radius) 

static LBPHFaceRecognizer  create () 

static new FaceRecognizer  __fromPtr__ (IntPtr addr) 

static Algorithm  __fromPtr__ (IntPtr addr) 

static IntPtr  ThrowIfNullIntPtr (IntPtr ptr) 

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


static 
◆ create() [1/6]
 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:
◆ 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:
◆ 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:
◆ 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:
◆ 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:
◆ 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:
◆ Dispose()
override void OpenCVForUnity.FaceModule.LBPHFaceRecognizer.Dispose 
( 
bool  disposing  ) 


protectedvirtual 
◆ getGridX()
int OpenCVForUnity.FaceModule.LBPHFaceRecognizer.getGridX 
( 
 ) 

◆ getGridY()
int OpenCVForUnity.FaceModule.LBPHFaceRecognizer.getGridY 
( 
 ) 

◆ getHistograms()
List< Mat > OpenCVForUnity.FaceModule.LBPHFaceRecognizer.getHistograms 
( 
 ) 

◆ getLabels()
Mat OpenCVForUnity.FaceModule.LBPHFaceRecognizer.getLabels 
( 
 ) 

◆ getNeighbors()
int OpenCVForUnity.FaceModule.LBPHFaceRecognizer.getNeighbors 
( 
 ) 

◆ getRadius()
int OpenCVForUnity.FaceModule.LBPHFaceRecognizer.getRadius 
( 
 ) 

◆ getThreshold()
double OpenCVForUnity.FaceModule.LBPHFaceRecognizer.getThreshold 
( 
 ) 

◆ setGridX()
void OpenCVForUnity.FaceModule.LBPHFaceRecognizer.setGridX 
( 
int  val  ) 

◆ setGridY()
void OpenCVForUnity.FaceModule.LBPHFaceRecognizer.setGridY 
( 
int  val  ) 

◆ setNeighbors()
void OpenCVForUnity.FaceModule.LBPHFaceRecognizer.setNeighbors 
( 
int  val  ) 

◆ setRadius()
void OpenCVForUnity.FaceModule.LBPHFaceRecognizer.setRadius 
( 
int  val  ) 

◆ setThreshold()
void OpenCVForUnity.FaceModule.LBPHFaceRecognizer.setThreshold 
( 
double  val  ) 

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