Update app.py

app.py

@@ -566,10 +566,6 @@ def infer_upscale(
         return None, seed, gr.update(), gr.update(), gr.update(), gr.update(), gr.update(visible=True, value="Please upload an image for upscaling.")
 
     try:
-
-        if input_image is None:
-            return None, seed
-
         if randomize_seed:
             seed = random.randint(0, MAX_SEED)
         
@@ -609,7 +605,12 @@ def infer_upscale(
         # resize to target desired size
         image = image.resize((w_original * upscale_factor, h_original * upscale_factor))
         
-
+        # Convert the image back to PIL Image and ensure proper scaling
+        if isinstance(image, torch.Tensor):
+            image = image.cpu().permute(1, 2, 0).numpy()
+        if image.max() <= 1.0:
+            image = (image * 255).astype(np.uint8)
+        image = Image.fromarray(image)
 
         return image, seed, num_inference_steps, upscale_factor, controlnet_conditioning_scale, gr.update(), gr.update(visible=False)
     except Exception as e: