class_docstr: Randomly crops an image based on self._sample_random_crop_region.
class_docstr_tok: ["Randomly","crops","an","image","based","on","self._sample_random_crop_region","."]
code: def __call__(self, features: Features) -> Features:
      new_features = super().__call__(dict(features))
      return self._drop_degenerate_features(new_features, features)
  
imports: import abc
  import dataclasses
  from typing import Optional, Sequence, Tuple, Union
  from clu import preprocess_spec
  from scenic.projects.owl_vit.preprocessing import modalities
  from scenic.projects.owl_vit.preprocessing import transforms
  import tensorflow
label_desc: Use image node_id 1 for calling the RandomCropBase obj's underlying member method code with example usage: obj.__call__(features) and returns: self