Update app.py

app.py

@@ -926,9 +926,9 @@ def text_to_image(prompt, model_id, steps, guidance_scale, progress=gr.Progress(
         import traceback
         traceback.print_exc()
         return None, error_msg
+        
 
 
-# === KORRIGIERTE HAUPTFUNKTION MIT RICHTIGEM COMPOSITING ===
 def img_to_image(image, prompt, neg_prompt, strength, steps, guidance_scale,
                  mode, bbox_x1, bbox_y1, bbox_x2, bbox_y2,
                  progress=gr.Progress()):
@@ -980,31 +980,42 @@ def img_to_image(image, prompt, neg_prompt, strength, steps, guidance_scale,
             print(f"ℹ️ Kein manueller Negativ-Prompt, verwende nur automatischen: {combined_negative_prompt}")
         
         print(f"✅ Finaler kombinierter Negativ-Prompt: {combined_negative_prompt}")
-        
 
-        # ===== GESICHTS-SPEZIFISCHE BOOSTER FÜR NUR-GESICHT MODUS =====
+        # ===== PROMPT-BOOSTER FÜR DREI MODI =====
         if mode == "face_only_change":
             face_boosters = "(perfect face:1.2), (symmetrical face:1.1), realistic shaded perfect face, "
             
             if not any(keyword in prompt.lower() for keyword in 
-                   ["perfect face", "symmetrical", "realistic face", "shaded face"]):
+                       ["perfect face", "symmetrical", "realistic face", "shaded face"]):
                 enhanced_prompt = face_boosters + prompt
                 print(f"👤 Gesichts-Booster hinzugefügt: {face_boosters}")
             else:
                 enhanced_prompt = prompt
                 print(f"👤 Benutzer hat bereits Gesichts-Booster im Prompt")
-        else:
-            enhanced_prompt = prompt
+                
+        elif mode == "focus_change":
+            focus_boosters = "(sharp focus:1.2), (detailed subject:1.1), (clear foreground:1.1), "
             
-
-        # ===== HINTERGRUND-BOOSTER FÜR UMGEBUNGS-ÄNDERUNG =====
-        if mode == "environment_change":
+            if not any(keyword in prompt.lower() for keyword in 
+                       ["sharp focus", "detailed subject", "clear foreground", "well-defined"]):
+                enhanced_prompt = focus_boosters + prompt
+                print(f"🎯 Focus-Booster hinzugefügt: {focus_boosters}")
+            else:
+                enhanced_prompt = prompt
+                print(f"🎯 Benutzer hat bereits Focus-Booster im Prompt")
+                
+        elif mode == "environment_change":
             background_boosters = "complete scene, full background, entire environment, "
             
-            if not any(keyword in enhanced_prompt.lower() for keyword in 
-                      ["complete scene", "full background", "entire environment", "whole setting"]):
-                enhanced_prompt = background_boosters + enhanced_prompt
+            if not any(keyword in prompt.lower() for keyword in 
+                       ["complete scene", "full background", "entire environment", "whole setting"]):
+                enhanced_prompt = background_boosters + prompt
                 print(f"🌳 Hintergrund-Booster hinzugefügt: {background_boosters}")
+            else:
+                enhanced_prompt = prompt
+                print(f"🌳 Benutzer hat bereits Hintergrund-Booster im Prompt")
+        else:
+            enhanced_prompt = prompt
 
         print(f"🎯 Finaler Prompt für {mode}: {enhanced_prompt}")
 
@@ -1073,7 +1084,6 @@ def img_to_image(image, prompt, neg_prompt, strength, steps, guidance_scale,
 
         # ===== CONTROLNET-INPAINTING PIPELINE =====
         pipe = load_img2img(keep_environment=keep_environment)
-        #pipe = load_img2img()  # MUSS StableDiffusionControlNetInpaintPipeline sein!
         
         # ===== SEED UND GENERATOR =====
         adj_guidance = min(guidance_scale, 12.0)
@@ -1086,8 +1096,8 @@ 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)
-
+        
+        # Berechne die Gewichtung basierend auf dem Modus
         if keep_environment:  # Depth + Canny
             conditioning_scale = [
                 controlnet_strength * 0.6,  # Depth: 60%
@@ -1114,7 +1124,6 @@ def img_to_image(image, prompt, neg_prompt, strength, steps, guidance_scale,
             callback_on_step_end_tensor_inputs=[],
         )
     
-
         print("✅ ControlNet-Inpainting abgeschlossen")
 
         # ===== KORREKTES COMPOSITING =====
@@ -1127,8 +1136,8 @@ def img_to_image(image, prompt, neg_prompt, strength, steps, guidance_scale,
                 inpaint_result=generated_image,
                 original_mask=original_mask,
                 padding_info=padding_info,
-                bbox_coords=(bbox_x1, bbox_y1, bbox_x2, bbox_y2),  # NEU!
-                mode=mode  # NEU!
+                bbox_coords=(bbox_x1, bbox_y1, bbox_x2, bbox_y2),
+                mode=mode
             )            
             print(f"✅ Korrektes Compositing durchgeführt")
         else: