class_docstr: Base class for image ops that require a random seed.
class_docstr_tok: ["Base","class","for","image","ops","that","require","a","random","seed","."]
docstr: Returns transformed boxes.
docstr_tok: ["Returns","transformed","boxes","."]
code: def apply_boxes(
      self,
      boxes: tf.Tensor,
      *,
      image_size: transforms.SizeTuple,  # pytype: disable=signature-mismatch
      seed: tf.Tensor,
  ) -> tf.Tensor:
      """Returns transformed boxes."""
      raise NotImplementedError(
          f"{self.__class__.__name__} is not implemented for bounding boxes."
      )
  
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 3 for calling the RandomImagePreprocessOp obj's underlying member method code with example usage: obj.apply_boxes(boxes) without return types