code: def subtract_mean_and_normalize(image, means, std, random=False):
      if len(means) != len(std):
          raise ValueError("len(means) and len(std) must match")
      image = image / 255
      if random:
          image = color_augmentations(image)
      image = (image - tf.constant(means)) / tf.constant(std)
      return image
  
imports: import functools
  import cv2
  import numpy
  import tensorflow
  from tensorflow_graphics.projects.points_to_3Dobjects.utils import image
  from google3.third_party.tensorflow_models.object_detection.core import preprocessor
label_desc: Use image node_id 8 for calling a global function with example usage: subtract_mean_and_normalize(image, means, std, random) and returns: image