  
  
  class ImageManipulation():
      """ Manipulations to be performed on training images """
      def __init__(self, input_size, output_size, coverage_ratio):
          """ input_size: Size of the face input into the model
              output_size: Size of the face that comes out of the modell
              coverage_ratio: Coverage ratio of full image. Eg: 256 * 0.625 = 160
          """
          logger.debug("Initializing %s: (input_size: %s, output_size: %s, coverage_ratio: %s)",
 
</s> remove         logger.debug("Initializing %s: (input_size: %s, output_size: %s, coverage_ratio: %s)",
                     self.__class__.__name__, input_size, output_size, coverage_ratio)
        # Transform args
        self.rotation_range = 10  # Range to randomly rotate the image by
        self.zoom_range = 0.05  # Range to randomly zoom the image by
        self.shift_range = 0.05  # Range to randomly translate the image by
        self.random_flip = 0.5  # Chance to flip the image horizontally
 </s> add         logger.debug("Initializing %s: (input_size: %s, output_size: %s, coverage_ratio: %s, "
                     "config: %s)", self.__class__.__name__, input_size, output_size,
                     coverage_ratio, config)
        self.config = config </s> remove         self.add_item(
            section=section, title="preview_images", datatype=int, default=14, min_max=(2, 16),
            rounding=2, fixed=False,
            info="Number of sample faces to display for each side in the preview when training.")
 </s> add  </s> remove     def __init__(self, model, use_mask, coverage_ratio, batchers):
 </s> add     def __init__(self, model, use_mask, coverage_ratio, preview_images, batchers): </s> remove         augment_color:      Perform random shifting of LAB colors
 </s> add         augment_color:      Perform random shifting of L*a*b* colors </s> remove         generator = TrainingDataGenerator(input_size, output_size, self.model.training_opts)
 </s> add         generator = TrainingDataGenerator(input_size,
                                          output_size,
                                          self.model.training_opts,
                                          self.config)
    def __init__(self, input_size, output_size, coverage_ratio, config):
  
  
  class ImageManipulation():
      """ Manipulations to be performed on training images """
    def __init__(self, input_size, output_size, coverage_ratio, config):
          """ input_size: Size of the face input into the model
              output_size: Size of the face that comes out of the modell
              coverage_ratio: Coverage ratio of full image. Eg: 256 * 0.625 = 160
          """
          logger.debug("Initializing %s: (input_size: %s, output_size: %s, coverage_ratio: %s)",
keep keep keep keep replace keep keep keep keep keep
 Expose Augmentation Options to config 
lib/training_data.py