class_docstr: Base class of Input processor.
class_docstr_tok: ["Base","class","of","Input","processor","."]
docstr: Normalize the image to zero mean and unit variance.
docstr_tok: ["Normalize","the","image","to","zero","mean","and","unit","variance","."]
code: def normalize_image(self):
      """Normalize the image to zero mean and unit variance."""
      # The image normalization is identical to Cloud TPU ResNet.
      self._image = tf.image.convert_image_dtype(
          self._image, dtype=tf.float32
      )
      offset = tf.constant([0.485, 0.456, 0.406])
      offset = tf.expand_dims(offset, axis=0)
      offset = tf.expand_dims(offset, axis=0)
      self._image -= offset
  
      scale = tf.constant([0.229, 0.224, 0.225])
      scale = tf.expand_dims(scale, axis=0)
      scale = tf.expand_dims(scale, axis=0)
      self._image /= scale
  
imports: from absl import logging
  import tensorflow
  import utils
  from pipeline import anchors
  from .None import preprocessor
  from .None import tf_example_decoder
label_desc: Use image node_id 2 for calling the InputProcessor obj's underlying member method code with example usage: obj.normalize_image() without return types