code: def _test_predict_func(self, input_images_batch):
      # For the test purpose, use entropy as the prediction, so images
      # with higher entropy produce higher model predictions. It works only,
      # when the input has only one image in the batch.
      entropy = pic.estimate_image_entropy(input_images_batch[0])
      return [entropy]
  
file_path: saliency/saliency/metrics/pic_test.py
imports: import numpy
  import os
  import unittest
  from .None import pic
  from pathlib import Path
  from PIL import Image
label_desc: Use image node_id 2 for calling the PicTest obj's underlying member method code with example usage: obj._test_predict_func(input_images_batch) and returns: list