code: def horizontal_flip_augmenter(
      image,
      annotation,
      random,
      skip_probability=_DEFAULT_AUG_PARAMS["skip_probability_flip"],
  ):
      if random.uniform(0.0, 1.0) < skip_probability:
          return image, annotation
  
      image_height, image_width, _ = image.shape
      flipped_image = np.flip(image, 1)
  
      # One image can have more than one annotation. so loop through annotations and flip across the horizontal axis
      for i in range(len(annotation)):
          # Only flip if the annotation is not an empty annotation.
          if np.any(annotation[i][1:5]):
              annotation[i][1] = 1 - annotation[i][1] - annotation[i][3]
  
      return flipped_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 6 for calling a global function with example usage: horizontal_flip_augmenter(image, annotation, random, skip_probability) and returns: flipped_image,  annotation, image,  annotation