code: def transform(image, npx=64, is_crop=True, resize_w=64):
      if is_crop:
          cropped_image = center_crop(image, npx, resize_w=resize_w)
      else:
          cropped_image = image
      return np.array(cropped_image) / 127.5 - 1.0
  
file_path: BigDL/apps/variational-autoencoder/utils.py
imports: import numpy
  import imageio
  from PIL import Image
label_desc: Use image node_id 2 for calling a global function with example usage: transform(image, npx, is_crop, resize_w) and returns: unknown