Update app.py

app.py

@@ -939,12 +939,26 @@ def img_to_image(image, prompt, neg_prompt, strength, steps, guidance_scale,
 
         # ===== CONTROLNET-GESTEUERTES INPAINTING DURCHFÜHREN =====
         print(f"🔄 Führe ControlNet-gesteuertes Inpainting durch...")
+        # Berechne die Gewichtung basierend auf dem Modus (wie in der alten ControlNet-Methode)
+
+        if keep_environment:  # Depth + Canny
+            conditioning_scale = [
+                controlnet_strength * 0.6,  # Depth: 60%
+                controlnet_strength * 0.4   # Canny: 40%
+            ]
+        else:  # OpenPose + Canny
+            conditioning_scale = [
+                controlnet_strength * 0.7,  # OpenPose: 70%
+                controlnet_strength * 0.3   # Canny: 30%
+            ]
+
         result = pipe(
             prompt=enhanced_prompt,
             negative_prompt=combined_negative_prompt,
-            image=scaled_image,          # Das skalierte Originalbild
-            mask_image=scaled_mask,      # Die skalierte Maske
-            control_image=controlnet_maps,  # Die ControlNet-Maps als Liste
+            image=scaled_image,
+            mask_image=scaled_mask,
+            control_image=controlnet_maps,
+            controlnet_conditioning_scale=conditioning_scale,  # DYNAMISCHE Liste
             strength=adj_strength,
             num_inference_steps=int(steps),
             guidance_scale=adj_guidance,
@@ -952,6 +966,7 @@ def img_to_image(image, prompt, neg_prompt, strength, steps, guidance_scale,
             callback_on_step_end=callback,
             callback_on_step_end_tensor_inputs=[],
         )
+    
 
         print("✅ ControlNet-Inpainting abgeschlossen")