Constructor

obj = cv.LBPHFaceRecognizer('OptionName',optionValue, ...)

Options

• 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. default 1
• 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. default 8
• GridX 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. default 8
• GridY 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. default 8
• Threshold The threshold applied in the prediction. If the distance to the nearest neighbor is larger than the threshold, the prediction returns -1. default realmax

Initializes this LBPH Model. The current implementation is rather fixed as it uses the Extended Local Binary Patterns per default.

Radius and Neighbors are used in the local binary patterns creation. GridX and GridY control the grid size of the spatial histograms.

Notes

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