Update app.py

app.py

@@ -9,11 +9,6 @@ codings_size = 100
 generator = from_pretrained_keras("huggan/crypto-gan")
 
 
-def post_process(image):
-    image = ((image + 1) / 2) # scale back
-    return image
-
-
 def generate(seed):
     noise = tf.random.normal(shape=[n_images, codings_size], seed=seed)
     generated_images = generator(noise, training=False)
@@ -21,7 +16,7 @@ def generate(seed):
     fig = plt.figure(figsize=(10, 10))
     for i in range(generated_images.shape[0]):
         plt.subplot(6, 6, i+1)
-        plt.imshow(post_process(generated_images[i, :, :, :]), cmap="binary")
+        plt.imshow(generated_images[i, :, :, :])
         plt.axis("off")
     return fig