          """ 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)",
                       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
          # Transform and Warp args
          self.input_size = input_size
          self.output_size = output_size
          # Warp args
          self.coverage_ratio = coverage_ratio  # Coverage ratio of full image. Eg: 256 * 0.625 = 160
 
</s> remove     def __init__(self, input_size, output_size, coverage_ratio):
 </s> add     def __init__(self, input_size, output_size, coverage_ratio, config): </s> remove         preview_images = self.config.get("preview_images", 14)
        preview_images = min(max(preview_images, 2), 16)
        self.training_opts["preview_images"] = preview_images
 </s> add  </s> remove     @staticmethod
    def random_lab(image):
        """ Perform random color/lightness adjustment in LAB colorspace """
        randoms = [(random() * 0.6) - 0.3,  # L adjust +/- 30%
                   (random() * 0.16) - 0.08,  # A adjust +/- 8%
                   (random() * 0.16) - 0.08]  # B adjust +/- 8%
 </s> add     def random_lab(self, image):
        """ Perform random color/lightness adjustment in L*a*b* colorspace """
        amount_l = self.config.get("color_lightness", 30) / 100
        amount_ab = self.config.get("color_ab", 8) / 100

        randoms = [(random() * amount_l * 2) - amount_l,  # L adjust
                   (random() * amount_ab * 2) - amount_ab,  # A adjust
                   (random() * amount_ab * 2) - amount_ab]  # B adjust </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)
        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
          """ 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, "
                     "config: %s)", self.__class__.__name__, input_size, output_size,
                     coverage_ratio, config)
        self.config = config
        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
        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
        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
        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
        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
        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
          # Transform and Warp args
          self.input_size = input_size
          self.output_size = output_size
          # Warp args
          self.coverage_ratio = coverage_ratio  # Coverage ratio of full image. Eg: 256 * 0.625 = 160
keep keep keep keep replace replace replace replace replace replace replace keep keep keep keep keep
 Expose Augmentation Options to config 
lib/training_data.py