code: def estimate_image_entropy(image: np.ndarray) -> float:
      """Estimates the amount of information in a given image.
  
      Args:
        image: an image, which entropy should be estimated. The dimensions of the
          array should be [H, W, C] or [H, W] of type uint8.
      Returns:
        The estimated amount of information in the image.
      """
      buffer = io.BytesIO()
      pil_image = Image.fromarray(image)
      pil_image.save(buffer, format="webp", lossless=True, quality=100)
      buffer.seek(0, os.SEEK_END)
      length = buffer.tell()
      buffer.close()
      return length
  
file_path: saliency/saliency/metrics/pic.py
imports: import io
  import numpy
  import os
  from PIL import Image
  from scipy import interpolate
  from typing import Callable, List, NamedTuple, Optional, Sequence, Tuple
label_desc: Use image node_id 3 for calling a global function with example usage: estimate_image_entropy(image) and returns: length