new_contents: import numpy as np
  
  
  def white_unbalance(x, y):
      # Adjust white balance.
      min_channel_high_end = 0.25
      max_channel_low_end = 0.25
      rmin = random.random()*min_channel_high_end
      gmin = random.random()*min_channel_high_end
      bmin = random.random()*min_channel_high_end
      rmax = random.random()*max_channel_low_end + 1 - max_channel_low_end
      gmax = random.random()*max_channel_low_end + 1 - max_channel_low_end
      bmax = random.random()*max_channel_low_end + 1 - max_channel_low_end
      new_image = np.empty((source.height, source.width, 3), dtype=np.float32)
      image = np.multiply(np.array(source), 1/255.)
  
      # Make exposure ocasionally brighter
      image = np.clip(np.multiply(image, random.random()*0.3+1.0), 0.0, 1.0)
  
      new_image[:, :, 0] = np.add(np.multiply(image[:, :, 0], (rmax-rmin)), rmin)
      new_image[:, :, 1] = np.add(np.multiply(image[:, :, 1], (gmax-gmin)), gmin)
      new_image[:, :, 2] = np.add(np.multiply(image[:, :, 2], (bmax-bmin)), bmin)
      new_image = np.multiply(new_image, 255)
      image = Image.fromarray(np.uint8(new_image))
      return image
  
  
  
subject: save work for augmentation