Update app.py

app.py

@@ -1017,32 +1017,73 @@ def img_to_image(image, prompt, neg_prompt, strength, steps, guidance_scale,
         ########################################################################
         if mode == "focus_change":
             keep_environment = False
- 
-            # OPTIMIERTE WERTE FÜR FOCUS_CHANGE
-            adj_strength = min(0.6, strength * 1.05)        # Konservativer (0.65)
-            controlnet_weight = 0.85                        # Stärkere ControlNet-Kontrolle
-            
-            #Controlnet gesteuertes Inpainting
-            pose_ratio = 0.8                                # OpenPose dominiert
-            canny_ratio = 0.2                               # Canny unterstützt
     
-            #controlnet_strength = adj_strength * controlnet_weight
-            controlnet_strength = min(0.6, controlnet_weight)
-
-            if any(k in prompt.lower() for k in ["anime", "cartoon", "fantasy", "fairy", "alien"]):
-                steps = max(steps, 35)
-                print(f"⚡ Steps verändert auf {steps} für bessere Details")
-
-
-            # KRITISCH FEHLT HIER:
+            # 1. DENOISING-STÄRKE
+            adj_strength = min(0.6, strength)
+    
+            # 2. CONTROLNET-STÄRKE (wie environment_change)
+            controlnet_strength = 0.5  # Stärkere ControlNet-Kontrolle für Focus
+    
+            # 3. DYNAMISCHE POSE:CANNY RATIO BASIEREND AUF PROMPT
+            prompt_lower = prompt.lower()
+    
+            # Keyword-Gruppen
+            humanoid_keywords = [
+                "anime", "cartoon", "manga", "witch", "wizard", "sorcerer",
+                "alien", "elf", "fairy", "character", "fantasy", "superhero",
+                "cyborg", "robot", "android", "santa", "person", "woman", "man",
+                "girl", "boy", "child", "business", "suit", "professional",
+                "sports", "athlete", "runner", "dancer", "portrait", "face"
+            ]
+    
+            object_keywords = [
+                "car", "vehicle", "automobile", "chair", "table", "desk",
+                "statue", "sculpture", "monument", "lamp", "bottle", "vase",
+                "product", "object", "furniture", "device", "tool", "item",
+                "building", "house", "tree", "plant", "rock", "stone"
+            ]
+    
+            animal_keywords = [
+                "dog", "cat", "wolf", "lion", "tiger", "bear", "rabbit",
+                "horse", "bird", "animal", "creature", "beast", "monkey",
+                "elephant", "giraffe", "zebra", "deer", "fox", "pet"
+            ]
+    
+            # Standard-Ratio
+            pose_ratio = 0.7     # 70%
+            canny_ratio = 0.3    # 30%
+    
+            # Anpassung für Humanoid → Humanoid
+            if any(keyword in prompt_lower for keyword in humanoid_keywords):
+                pose_ratio = 0.90 # 85% Pose
+                canny_ratio = 0.10 # 15% Canny
+                print("👤 Humanoid → Humanoid → Ratio 85:15 (Pose:Canny)")
+    
+            # Anpassung für Gegenstand → Gegenstand
+            elif any(keyword in prompt_lower for keyword in object_keywords):
+                pose_ratio = 0.20 # 25% Pose
+                canny_ratio = 0.80 # 75% Canny
+                adj_strength = min(0.7, strength * 1.15)  # Stärkere Transformation
+                print("📦 Gegenstand → Gegenstand → Ratio 25:75 (Pose:Canny)")
+    
+            # Anpassung für Mensch → Tier
+            elif any(keyword in prompt_lower for keyword in animal_keywords):
+                pose_ratio = 0.5   # 50% Pose
+                canny_ratio = 0.5  # 50% Canny
+                adj_strength = min(0.65, strength * 1.1)  # Etwas stärker
+                print("🐾 Mensch → Tier → Ratio 50:50 (Pose:Canny)")
+    
+            # CONDITIONING SCALE BERECHNEN (genau wie environment_change)
             conditioning_scale = [
-                controlnet_strength * pose_ratio,  # Für OpenPose
-                controlnet_strength * canny_ratio  # Für Canny
+                controlnet_strength * pose_ratio,  # OpenPose
+                controlnet_strength * canny_ratio  # Canny
             ]
-          
-            print(f"🎯 OPTIMIERTER MODUS: Focus verändern")
-            print(f"   Strength: {adj_strength:.2f}, ControlNet: {controlnet_strength:.3f}")
+    
+            print(f"🎯 MODUS: Focus verändern")
+            print(f"   Strength: {adj_strength}, ControlNet: {controlnet_strength}")
             print(f"   OpenPose: {pose_ratio*100}%, Canny: {canny_ratio*100}%")
+            print(f"   Conditioning Scale: [{conditioning_scale[0]:.3f}, {conditioning_scale[1]:.3f}]")     
+        
 
         elif mode == "environment_change":
             keep_environment = True