new_contents: #!/usr/bin/env python3
  
  import argparse
  import pickle
  import keras
  import numpy as np
  import sys
  
  parser = argparse.ArgumentParser(description='Train the network given ')
  
  parser.add_argument('-b', '--database-path', dest='imgdb_path',
                      help='Path to the image database containing test data.'
                           'Default is img.db in current folder.')
  parser.add_argument('-m', '--model-path', dest='model_path',
                      help='Store the trained model using this path. Default is model.h5.')
  
  
  args = parser.parse_args()
  
  imgdb_path = "img.db"
  model_path = "model.h5"
  res = {"x": 16, "y": 16}
  
  if args.model_path is not None:
      model_path = args.model_path
  
  if args.imgdb_path is not None:
      imgdb_path = args.imgdb_path
  
  with open(imgdb_path, "rb") as f:
      mean = pickle.load(f)
      print("mean=" + str(mean))
      x = pickle.load(f)
      y = pickle.load(f)
  
  model = keras.models.load_model(model_path)
  
  print(model.summary())
  
  result = model.evaluate(x, y)
  
  print("Evaluation result")
  print("=================")
  
  print("loss: {} precision: {}".format(result[0], result[1]))
  
  
  
subject: Add simple script to evaluate the given network