fix

api_routes.py

@@ -1126,6 +1126,48 @@ async def analyze_face(
         }
 
 
+@api_router.post("/detect_faces", tags=["Face API"])
+@log_api_params
+async def detect_faces_endpoint(
+    file: UploadFile = File(..., description="需要进行人脸检测的图片"),
+):
+    """
+    上传单张图片，调用 YOLO（_detect_faces）做人脸检测并返回耗时。
+    """
+    if not file or not file.content_type or not file.content_type.startswith("image/"):
+        raise HTTPException(status_code=400, detail="请上传有效的图片文件")
+
+    image_bytes = await file.read()
+    if not image_bytes:
+        raise HTTPException(status_code=400, detail="图片内容为空")
+
+    np_arr = np.frombuffer(image_bytes, np.uint8)
+    image = cv2.imdecode(np_arr, cv2.IMREAD_COLOR)
+    if image is None:
+        raise HTTPException(status_code=400, detail="无法解析图片文件，请确认格式正确")
+
+    if analyzer is None:
+        _ensure_analyzer()
+    if analyzer is None:
+        raise HTTPException(status_code=500, detail="人脸检测模型尚未就绪，请稍后再试")
+
+    detect_start = time.perf_counter()
+    try:
+        face_boxes = analyzer._detect_faces(image)
+    except Exception as exc:
+        logger.error(f"Face detection failed: {exc}")
+        raise HTTPException(status_code=500, detail="调用人脸检测失败") from exc
+    detect_duration = time.perf_counter() - detect_start
+
+    return {
+        "success": True,
+        "face_count": len(face_boxes),
+        "boxes": face_boxes,
+        "elapsed_ms": round(detect_duration * 1000, 3),
+        "elapsed_seconds": round(detect_duration, 4),
+    }
+
+
 @api_router.post(path="/analyze")
 @log_api_params
 async def analyze_face(