违停检测模型改为yolov8s，检测模式修改为手动框选禁停区域

apps/server/api/detection.py

@@ -21,11 +21,12 @@ async def detect_image(
     confidence: float = Query(0.5),
     iou: float = Query(0.45),
     algorithm_config: Optional[str] = Query(None, description="算法配置JSON字符串"),
-    composite: bool = Query(False, description="是否启用复合检测（火灾检测时同时检测火焰和烟雾）")
+    composite: bool = Query(False, description="是否启用复合检测（火灾检测时同时检测火焰和烟雾）"),
+    region_polygon: Optional[str] = Query(None, description="禁停区域多边形JSON，例如：[[x1,y1],[x2,y2],...]")
 ):
     """
     图片检测接口
-    
+
     Args:
         algorithm_config: 算法配置JSON，例如：
             {
@@ -36,6 +37,7 @@ async def detect_image(
                 "loitering_threshold": 300.0,
                 "movement_threshold": 5.0
             }
+        region_polygon: 禁停区域多边形坐标，用于违停检测
     """
     from main import model_service
     from services.detection_service import DetectionService
@@ -49,19 +51,27 @@ async def detect_image(
             algo_config = json.loads(algorithm_config)
         except json.JSONDecodeError as e:
             logger.warning(f"算法配置解析失败: {e}")
-    
+
+    # 解析禁停区域
+    region = None
+    if region_polygon:
+        try:
+            region = json.loads(region_polygon)
+        except json.JSONDecodeError as e:
+            logger.warning(f"禁停区域解析失败: {e}")
+
     try:
         contents = await file.read()
         nparr = np.frombuffer(contents, np.uint8)
         frame = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
-        
+
         if frame is None:
             return ImageDetectionResult(
                 success=False,
                 message="无法读取图片",
                 data={}
             )
-        
+
         # 判断是否启用复合火灾检测
         if composite and model_id == 'fire_detection':
             result = await detection_service.detect_fire_composite(
@@ -69,7 +79,9 @@ async def detect_image(
             )
         else:
             result = await detection_service.detect_image(
-                frame, model_id, confidence, iou, algorithm_config=algo_config
+                frame, model_id, confidence, iou,
+                algorithm_config=algo_config,
+                region_polygon=region
             )
         
         if result['success']: