class_docstr: Abstract generator class.
      
docstr: Compute target outputs for the network using images and their annotations.
          
code: def compute_targets(self, image_group, annotations_group):
      """Compute target outputs for the network using images and their annotations."""
      # get the max image shape
      max_shape = tuple(
          max(image.shape[x] for image in image_group) for x in range(3)
      )
      anchors = self.generate_anchors(max_shape)
  
      batches = self.compute_anchor_targets(
          anchors, image_group, annotations_group, self.num_classes()
      )
  
      return list(batches)
  
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 26 for calling the Generator obj's underlying member method code with example usage: obj.compute_targets(image_group, annotations_group) and returns: list