text: from pix2pix_model import Pix2Pix
  from PIL import Image
  import tensorflow as tf
  import numpy as np
  
  print("Loading Pix2Pix checkpoint..")
  model = Pix2Pix({'checkpoint': 'last.h5'}).model
  # model = Pix2Pix({'checkpoint': None}).model
  
  # input_image = Image.open('/Users/nono/Desktop/flower.jpg')
  input_image = Image.open('/Users/nono/Desktop/flower2.png')
  
  # ↓
  # Pre-processing input
  img_in = tf.image.convert_image_dtype(np.array(input_image), tf.float32)
  img_in = tf.image.resize(img_in, (256, 256), antialias=True)
  img_in = tf.expand_dims(img_in, axis=[0]) # (1, 256, 256, 3)
  # ↓
  # Predict
  print("Predicting..")
  prediction = model(img_in, training=True)
  # ↓
  # Remap output from (-1.0, +1.0) to (0, 255)
  img_out = prediction[0] # -> (256, 256, 3)
  img_out = (img_out * 0.5 + 0.5) * 255.0
  img_out = tf.cast(img_out, tf.uint8)
  
  # Construct a PIL image to display in Runway
  output_image = Image.fromarray(np.array(img_out))
  
  output_image.save('/Users/nono/Desktop/output.jpg')