class_docstr: Abstract generator class.
      
docstr: Randomly transforms each image and its annotations.
          
code: def random_transform_group(self, image_group, annotations_group):
      """Randomly transforms each image and its annotations."""
  
      assert len(image_group) == len(annotations_group)
  
      for index in range(len(image_group)):
          # transform a single group entry
          (
              image_group[index],
              annotations_group[index],
          ) = self.random_transform_group_entry(
              image_group[index], annotations_group[index]
          )
  
      return image_group, annotations_group
  
imports: import numpy
  import random
  import warnings
  from tensorflow import keras
  from ..utils.anchors import anchor_targets_bbox, anchors_for_shape, guess_shapes
  from ..utils.config import parse_anchor_parameters, parse_pyramid_levels
  from ..utils.image import TransformParameters, adjust_transform_for_image, apply_transform, preprocess_image, resize_image
  from ..utils.transform import transform_aabb
label_desc: Use image node_id 19 for calling the Generator obj's underlying member method code with example usage: obj.random_transform_group(image_group, annotations_group) and returns: image_group,  annotations_group