Update app.py

app.py

@@ -553,33 +553,19 @@ def run_lora(prompt, cfg_scale, steps, selected_info_1, selected_info_2, selecte
                 progress_bar = f'<div class="progress-container"><div class="progress-bar" style="--current: {step_counter}; --total: {steps};"></div></div>'
                 yield image, seed, gr.update(value=progress_bar, visible=True)
 
-            if image_input is not None:
-               final_image = generate_image_to_image(prompt_mash, image_input, image_strength, steps, cfg_scale, width, height, seed)
-               print(f"Debug: generate_image_to_image output type: {type(final_image)}")  # Debugging
-               if not isinstance(final_image, (PIL.Image.Image, torch.Tensor)):  # Check if it's an image
-                    print(f"Error: Expected an image, but got {type(final_image)}")
-                    raise ValueError("Expected an image from generate_image_to_image, but got a non-image value.")
-            print(f"Debug: generate_image_to_image output value: {final_image}")  # Debugging
-            yield final_image, seed, gr.update(visible=False)
-        
-        if final_image is None:
-            print("No final image generated.")  # Debugging statement
-        else:
-            print(f"Debug: final_image type: {type(final_image)}")  # Debugging
-            if not isinstance(final_image, (PIL.Image.Image, torch.Tensor)):  # Check if it's an image
-                print(f"Error: Expected an image, but got {type(final_image)}")
-                raise ValueError("Expected an image, but got a non-image value.")
-        print(f"Debug: final_image value: {final_image}")  # Debugging
-
-yield final_image, seed, gr.update(value=progress_bar, visible=False)
+            if final_image is None:
+                print("No final image generated.")  # Debugging statement
+            else:
+                print(f"Debug: final_image type: {type(final_image)}")  # Debugging
+                yield final_image, seed, gr.update(value=progress_bar, visible=False)
 
-    
     except Exception as e:
         print(f"Error during image generation: {e}")  # Error handling
         raise gr.Error("An error occurred during image generation.")
 
 run_lora.zerogpu = True
 
+
 def get_huggingface_safetensors(link):
     split_link = link.split("/")
     if len(split_link) == 4: