code: def hflip(features):
      """Flip an image, boxes [xyxy un-normalized] (, and masks) horizontally."""
      image = features["inputs"]
      target = features["label"]
  
      flipped_image = tf.image.flip_left_right(image)
  
      if "boxes" in target:
          # Flips the boxes.
          _, w = get_hw(image, dtype=tf.float32)
          x0, y0, x1, y1 = tf.split(target["boxes"], 4, axis=-1)
          # Converts as [w - x1, y0, w - x0, y1] not [w - x1 - 1, w - x0 - 1, y1]
          # because these are float coordinates not pixel indices.
          target["boxes"] = tf.concat([w - x1, y0, w - x0, y1], axis=-1)
  
      if "masks" in target:
          target["masks"] = tf.image.flip_left_right(target["masks"])
  
      features["inputs"] = flipped_image
      features["label"] = target
      return features
  
imports: from typing import Any, Dict
  import tensorflow
label_desc: Use image node_id 5 for calling a global function with example usage: hflip(features) and returns: features