Update app.py

app.py

@@ -6,7 +6,7 @@ num_rows = 3
 num_cols = 3
 num_images = num_rows * num_cols
 image_size = 64
-plot_image_size = 256
+plot_image_size = 64
 
 model = hf_hub.from_pretrained_keras("beresandras/denoising-diffusion-model")
 
@@ -46,7 +46,10 @@ def generate_images(diffusion_steps, stochasticity, min_signal_rate, max_signal_
         )
         
     # denormalize
-    generated_images = tf.clip_by_value(0.5 + 0.3 * pred_images, 0.0, 1.0)
+    data_mean = tf.constant([[[[0.4704 0.3942 0.3033]]]])
+    data_variance = tf.constant([[[[0.08366 0.05590 0.07183]]]])
+    generated_images = data_mean + pred_images * data_variance ** 0.5
+    generated_images = tf.clip_by_value(pred_images, 0.0, 1.0)
     
     # make grid
     generated_images = tf.image.resize(generated_images, (plot_image_size, plot_image_size), method="nearest")