Update controlnet_module.py

controlnet_module.py

@@ -1010,7 +1010,7 @@ class ControlNetProcessor:
                         area_score = optimal_max / area_ratio  # Starke Bestrafung für zu groß
 
 
-                    # 2. BBOX-ÜBERLAPPUNG
+                    # 2. BBOX-ÜBERLAPPUNG (wie gut überlappt die SAM-Maske die BBox)
                     bbox_mask = np.zeros((image.height, image.width), dtype=np.uint8)
                     bbox_mask[bbox_y1:bbox_y2, bbox_x1:bbox_x2] = 1
                     overlap = np.sum(mask_binary & bbox_mask)
@@ -1051,7 +1051,6 @@ class ControlNetProcessor:
                         
         
                     confidence_score = mask_max
-                    bbox_score = bbox_overlap_ratio
                        
                     score = (
                         bbox_overlap_ratio * 0.5 +      # 50% BBox-Überlappung (vorher 20%)