Trains a facemark model

success = obj.training(images, landmarks, configFile, scale)
success = obj.training(..., 'OptionName',optionValue, ...)

Input

• images cell-array of images which are used in training samples.
• landmarks cell-array of cell-array of points which stores the landmarks detected in a particular image.
• configFile name of the file storing parameters for training the model. For an example, see the |facemark_kazemi_train_config_demo.m| sample.
• scale size to which all images and landmarks have to be scaled to [w,h].

Output

• success returns true if the model is trained properly or false if it is not trained.

Options

• ModelFilename name of the trained model file that has to be saved. default 'face_landmarks.dat'

Trains a facemark model using gradient boosting to get a cascade of regressors which can then be used to predict shape.