Update controlnet_module.py

controlnet_module.py

@@ -1018,21 +1018,6 @@ class ControlNetProcessor:
                     overlap = np.sum(mask_binary & bbox_mask)
                     bbox_overlap_ratio = overlap / bbox_area if bbox_area > 0 else 0  # WICHTIG: durch bbox_area!
         
-                    
-        
-                    # Optimale Kopfgröße: 80-120% der BBox
-                    if area_ratio < 0.6:
-                        print(f"     ⚠️  Fläche zu klein für Kopf (<60% der BBox)")
-                        area_score = area_ratio * 0.5  # Stark bestrafen
-                    elif area_ratio > 1.5:
-                        print(f"     ⚠️  Fläche zu groß für Kopf (>150% der BBox)")
-                        area_score = 2.0 - area_ratio  # Linear bestrafen
-                    elif 0.8 <= area_ratio <= 1.2:
-                        area_score = 1.0  # Perfekte Größe
-                        print(f"     ✅ Perfekte Kopfgröße (80-120% der BBox)")
-                    else:
-                        # Sanfte Abweichung
-                        area_score = 1.0 - abs(area_ratio - 1.0) * 0.5
                         
         
                     # 2. KOMPAKTHEIT/SOLIDITÄT (30%)
@@ -1063,9 +1048,11 @@ class ControlNetProcessor:
                         print(f"     🎯 Kompaktheits-Analyse:")
                         print(f"       • Solidität (Fläche/Konvex): {solidity:.3f}")
                         print(f"       • Exzentrizität (Form): {eccentricity:.3f}")
-                        print(f"       • Kompaktheits-Score: {compactness_score:.
+                        print(f"       • Kompaktheits-Score: {compactness_score:.3f}")
+
+                        
         
-               
+                    confidence_score = mask_max
                        
                     score = (
                         bbox_overlap_ratio * 0.5 +      # 50% BBox-Überlappung (vorher 20%)
@@ -1077,7 +1064,6 @@ class ControlNetProcessor:
                     print(f"     📊 GESICHTS-SCORES für Maske {i+1}:")
                     print(f"       • Flächen-Score: {area_score:.3f}")
                     print(f"       • Kompaktheits-Score: {compactness_score:.3f}")
-                    print(f"       • BBox-Überlappungs-Score: {bbox_score:.3f}")
                     print(f"       • Konfidenz-Score: {confidence_score:.3f}")
                     print(f"       • GESAMTSCORE: {score:.3f}")