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character_detection.py

@@ -55,7 +55,7 @@ class CharacterDetector:
             d.mkdir(parents=True, exist_ok=True)
     
     def extract_faces_embeddings(self, *, start_offset_sec: float = 3.0, extract_every_sec: float = 0.5,
-                                 detector_backend: str = 'mtcnn', min_face_area: int = 400,
+                                 detector_backend: str = 'retinaface', min_face_area: int = 100,
                                  enforce_detection: bool = False) -> List[Dict[str, Any]]:
         """
         Extrae caras del vídeo y calcula sus embeddings usando DeepFace directamente.
@@ -117,9 +117,14 @@ class CharacterDetector:
                             except Exception:
                                 pass
                             
-                            # Guardar el frame completo
-                            save_path = self.faces_dir / f"frame_{saved_count:04d}.jpg"
-                            cv2.imwrite(str(save_path), frame)
+                            # Guardar recorte de la cara (mejor para UI y clustering visual)
+                            x = int(facial_area.get('x', 0)); y = int(facial_area.get('y', 0))
+                            w = int(facial_area.get('w', 0)); h = int(facial_area.get('h', 0))
+                            x2 = max(0, x); y2 = max(0, y)
+                            x3 = min(frame.shape[1], x + w); y3 = min(frame.shape[0], y + h)
+                            crop = frame[y2:y3, x2:x3] if (x3 > x2 and y3 > y2) else frame
+                            save_path = self.faces_dir / f"face_{saved_count:04d}.jpg"
+                            cv2.imwrite(str(save_path), crop)
                             
                             embeddings_caras.append({
                                 "embeddings": embedding,