Update app.py

app.py

@@ -1421,105 +1421,36 @@ def img_to_image(image, prompt, neg_prompt, strength, steps, guidance_scale,
 
 
             if any(keyword in prompt_lower for keyword in anime_keywords):
-    print("🎨 ANIME-TRANSFORM-MODUS")
-
-    def smoothstep(min_val, max_val, x):
-    x = max(0, min(1, (x - min_val) / (max_val - min_val)))
-    return x * x * (3 - 2 * x)
-
-    # 1️⃣ Transformationsdruck (radikal erst spät)
-    adj_strength = 0.30 + 0.55 * smoothstep(0.35, 0.9, ui_strength)
-    adj_strength = max(0.3, min(adj_strength, 0.85))
-
-    # 2️⃣ ControlNet: lange frei, dann stabilisieren
-    controlnet_strength = 0.30 + 0.52 * smoothstep(0.65, 0.9, ui_strength)
-    controlnet_strength = max(0.25, min(controlnet_strength, 0.85))
-
-    # 3️⃣ Anime-Ratios (normiert!)
-    depth_ratio = 0.55 + 0.15 * smoothstep(0.5, 0.9, ui_strength)
-    canny_ratio = 1.0 - depth_ratio
-
-    # 4️⃣ Conditioning
-    conditioning_scale = [
-        controlnet_strength * depth_ratio,
-        controlnet_strength * canny_ratio
-    ]
-
-    print(f"UI Strength: {ui_strength}")
-    print(f"adj_strength: {adj_strength:.3f}")
-    print(f"controlnet_strength: {controlnet_strength:.3f}")
-    print(f"Depth: {depth_ratio*100:.1f}%, Canny: {canny_ratio*100:.1f}%")
-    print(f"conditioning_scale: {conditioning_scale}")
-            
-
-
-            if any(keyword in prompt_lower for keyword in anime_keywords):
-                # Anime: Mehr Denoising für Stiländerungen
-                adj_strength = 0.55 + (ui_strength * 0.3)  # 0.2-1.0
-
+                print("🎨 ANIME-TRANSFORM-MODUS")
 
-                if ui_strength > 0.6:  # Bei radikalen Änderungen
-                    controlnet_strength = 0.3 + (ui_strength * 0.4)  # 0.3 → 0.66
-                else:  # Bei milden Änderungen
-                    controlnet_strength = 0.65 - (ui_strength * 0.3)  # 0.65 → 0.35
-        
-        
-                # Anime: Weniger Depth, mehr Canny
-                depth_ratio = 0.7 - (ui_strength * 0.2)  # 0.6 → 0.3
-                canny_ratio = 0.1 + (ui_strength * 0.1)  # 0.4 → 0.8
+                def smoothstep(min_val, max_val, x):
+                    x = max(0, min(1, (x - min_val) / (max_val - min_val)))
+                    return x * x * (3 - 2 * x)
 
-                #Clipping
+                # 1️⃣ Transformationsdruck (radikal erst spät)
+                adj_strength = 0.30 + 0.55 * smoothstep(0.35, 0.9, ui_strength)
                 adj_strength = max(0.3, min(adj_strength, 0.85))
-                controlnet_strength = max(0.25, min(controlnet_strength, 0.75))
-                depth_ratio = max(0.4, min(depth_ratio, 0.8))
-                canny_ratio = max(0.05, min(canny_ratio, 0.15))
-                
-
-                conditioning_scale = [
-                    controlnet_strength * depth_ratio,
-                    controlnet_strength * canny_ratio
-                ]
-        
-                print("   🎨 Anime-Modus: Mehr Freiheit für Stiländerungen")
-                print(f"   Strength: {adj_strength}, ControlNet: {controlnet_strength}")
-                print(f"   Depth: {depth_ratio*100}%, Canny: {canny_ratio*100}%")
-                print(f"   Conditioning Scale: [{conditioning_scale[0]:.3f}, {conditioning_scale[1]:.3f}]")
-
-
-            if any(keyword in prompt_lower for keyword in anime_keywords):
-                # Anime: Mehr Denoising für Stiländerungen
-                adj_strength = 0.55 + (ui_strength * 0.3)  # 0.2-1.0
 
+                # 2️⃣ ControlNet: lange frei, dann stabilisieren
+                controlnet_strength = 0.30 + 0.52 * smoothstep(0.65, 0.9, ui_strength)
+                controlnet_strength = max(0.25, min(controlnet_strength, 0.85))
 
-                if ui_strength > 0.6:  # Bei radikalen Änderungen
-                    controlnet_strength = 0.3 + (ui_strength * 0.4)  # 0.3 → 0.66
-                else:  # Bei milden Änderungen
-                    controlnet_strength = 0.65 - (ui_strength * 0.3)  # 0.65 → 0.35
-        
-        
-                # Anime: Weniger Depth, mehr Canny
-                depth_ratio = 0.7 - (ui_strength * 0.2)  # 0.6 → 0.3
-                canny_ratio = 0.1 + (ui_strength * 0.1)  # 0.4 → 0.8
-
-                #Clipping
-                adj_strength = max(0.3, min(adj_strength, 0.85))
-                controlnet_strength = max(0.25, min(controlnet_strength, 0.75))
-                depth_ratio = max(0.4, min(depth_ratio, 0.8))
-                canny_ratio = max(0.05, min(canny_ratio, 0.15))
-                
+                # 3️⃣ Anime-Ratios (normiert!)
+                depth_ratio = 0.55 + 0.15 * smoothstep(0.5, 0.9, ui_strength)
+                canny_ratio = 1.0 - depth_ratio
 
+                # 4️⃣ Conditioning
                 conditioning_scale = [
                     controlnet_strength * depth_ratio,
                     controlnet_strength * canny_ratio
                 ]
-        
-                print("   🎨 Anime-Modus: Mehr Freiheit für Stiländerungen")
-                print(f"   Strength: {adj_strength}, ControlNet: {controlnet_strength}")
-                print(f"   Depth: {depth_ratio*100}%, Canny: {canny_ratio*100}%")
-                print(f"   Conditioning Scale: [{conditioning_scale[0]:.3f}, {conditioning_scale[1]:.3f}]")
-
-
 
+                print(f"UI Strength: {ui_strength}")
+                print(f"adj_strength: {adj_strength:.3f}")
+                print(f"controlnet_strength: {controlnet_strength:.3f}")
+                print(f"Depth: {depth_ratio*100:.1f}%, Canny: {canny_ratio*100:.1f}%")
+                print(f"conditioning_scale: {conditioning_scale}")
+            
              
             elif any(keyword in prompt_lower for keyword in drawing_keywords):       
                 # Weniger Denoising für anatomische Korrektheit