code: def preprocess_train_example(
      example,
      camera_name="image_main",
      dtype=tf.float32,
      zero_centering=True,
  ):
      """Preprocesses the given video.
  
      Args:
        example: dict; Example that has an 'image_main'.
        camera_name: Name of the image sequence to use.
        dtype: Tensorflow data type; Data type of the image.
        zero_centering: If True, frames are normalized to values in [-1, 1].
          If False, values in [0, 1].
  
      Returns:
        dict; Example that has an 'inputs'.
      """
      frames = example[camera_name]
      frames = processors.normalize_image(frames, zero_centering, dtype)
      return {"inputs": frames}
  
file_path: scenic/scenic/dataset_lib/bair_dataset.py
imports: import functools
  from typing import Optional
  from absl import logging
  from dmvr import processors
  from flax import jax_utils
  import jax.numpy
  from scenic.dataset_lib import dataset_utils
  from scenic.dataset_lib import datasets
  import tensorflow
label_desc: Use image node_id 1 for calling a global function with example usage: preprocess_train_example(example, camera_name, dtype, zero_centering) and returns: dict