code: def color_augmenter(
      image,
      annotation,
      random_alpha_tf,
      max_brightness=_DEFAULT_AUG_PARAMS["max_brightness"],
      max_contrast=_DEFAULT_AUG_PARAMS["max_contrast"],
      max_saturation=_DEFAULT_AUG_PARAMS["max_saturation"],
  ):
      tf = _lazy_import_tensorflow()
      # Apply the random adjustment to brightness.
      brightness_delta = interpolate(
          random_alpha_tf[0], -max_brightness, max_brightness
      )
      image = tf.image.adjust_brightness(image, brightness_delta)
  
      # Apply the random adjustment to contrast.
      saturation_delta = interpolate(
          random_alpha_tf[1], 1 / max_saturation, max_saturation
      )
      image = tf.image.adjust_saturation(image, saturation_delta)
  
      # Apply random adjustment to saturation.
      contrast_delta = interpolate(
          random_alpha_tf[2], 1 / max_contrast, max_contrast
      )
      image = tf.image.adjust_contrast(image, contrast_delta)
  
      image = tf.clip_by_value(image, 0, 1)
  
      # No geometry changes, so just copy the annotations.
      return image, annotation
  
imports: from __future__ import print_function
  from __future__ import division
  from __future__ import absolute_import
  import numpy
  from PIL import Image
  import turicreate.toolkits._tf_utils
  import turicreate
  from turicreate._deps.minimal_package import _minimal_package_import_check
label_desc: Use image node_id 4 for calling a global function with example usage: color_augmenter(image, annotation, random_alpha_tf, max_brightness, max_contrast, max_saturation) and returns: image,  annotation