Update app.py

app.py

@@ -201,7 +201,6 @@ def inference(
         pipe = load_models(controlnet_model, diffusion_model)
         progress(0.5, desc="Models downloaded, preparing for inference...")
         
-        
         if prompt is None or prompt == "":
             raise gr.Error("Prompt is required")
 
@@ -211,7 +210,7 @@ def inference(
         pipe.scheduler = SAMPLER_MAP[sampler](pipe.scheduler.config)
 
         if seed == -1:
-            seed = torch.randint(0, 2**32 - 1, (1,)).item()
+            seed = torch.seed()  # Generate a truly random seed
         generator = torch.manual_seed(seed)
 
         if qr_code_content != "" or qrcode_image.size == (1, 1):
@@ -226,10 +225,10 @@ def inference(
             qr.make(fit=True)
 
             qrcode_image = qr.make_image(fill_color=qr_color, back_color=bg_color)
-            qrcode_image = resize_for_condition_image(qrcode_image, 768)
+            qrcode_image = resize_for_condition_image(qrcode_image, 1024)
         else:
             print("Using QR Code Image")
-            qrcode_image = resize_for_condition_image(qrcode_image, 768)
+            qrcode_image = resize_for_condition_image(qrcode_image, 1024)
 
         # Determine which image to use as init_image and control_image
         if use_qr_code_as_init_image:
@@ -269,8 +268,11 @@ def inference(
             final_image = invert_image(final_image)
         
         return final_image, seed
+    except gr.Error as e:
+        print(f"Gradio error in inference: {str(e)}")
+        return Image.new('RGB', (1024, 1024), color='white'), -1
     except Exception as e:
-        print(f"Error in inference: {str(e)}")
+        print(f"Unexpected error in inference: {str(e)}")
         return Image.new('RGB', (1024, 1024), color='white'), -1
 
 def invert_init_image_display(image):