feat: 新增人员徘徊/静止行为分析功能

本次提交实现了完整的人员行为分析系统，包括：
1. 新增基于位置和跟踪ID的两种行为检测算法
2. 新增徘徊检测服务与行为处理器模块
3. 前后端集成算法配置界面与告警展示
4. 支持图片和视频流场景下的行为分析
5. 新增算法配置接口与文档说明

具体改动：
- 新增loitering_detection模型目录与算法实现
- 新增AlgorithmConfig组件实现可视化配置
- 扩展图片/视频检测接口支持算法参数传递
- 新增行为告警推送与前端展示页面
- 优化检测服务，集成行为分析逻辑
- 移除冗余日志输出，完善代码注释

apps/server/api/detection.py

@@ -2,24 +2,50 @@ import cv2
 import numpy as np
 import base64
 import logging
+import json
+from typing import Optional
 from fastapi import APIRouter, UploadFile, File, Form, Query
 from models.schemas import ImageDetectionResult
 
 router = APIRouter()
 logger = logging.getLogger(__name__)
 
+
 @router.post("/detect/image", response_model=ImageDetectionResult)
 async def detect_image(
     file: UploadFile = File(...),
     model_id: str = Query("fire_detection"),
     confidence: float = Query(0.5),
-    iou: float = Query(0.45)
+    iou: float = Query(0.45),
+    algorithm_config: Optional[str] = Query(None, description="算法配置JSON字符串")
 ):
+    """
+    图片检测接口
+    
+    Args:
+        algorithm_config: 算法配置JSON，例如：
+            {
+                "enable_stationary_detection": true,
+                "enable_loitering_detection": false,
+                "stationary_threshold": 10.0,
+                "position_tolerance": 50,
+                "loitering_threshold": 300.0,
+                "movement_threshold": 5.0
+            }
+    """
     from main import model_service
     from services.detection_service import DetectionService
     
     detection_service = DetectionService(model_service)
     
+    # 解析算法配置
+    algo_config = None
+    if algorithm_config:
+        try:
+            algo_config = json.loads(algorithm_config)
+        except json.JSONDecodeError as e:
+            logger.warning(f"算法配置解析失败: {e}")
+    
     try:
         contents = await file.read()
         nparr = np.frombuffer(contents, np.uint8)
@@ -32,10 +58,14 @@ async def detect_image(
                 data={}
             )
         
-        result = await detection_service.detect_image(frame, model_id, confidence, iou)
+        result = await detection_service.detect_image(
+            frame, model_id, confidence, iou, algorithm_config=algo_config
+        )
         
         if result['success']:
-            annotated_frame = detection_service.draw_detections(frame, result['detections'])
+            annotated_frame = detection_service.draw_detections(
+                frame, result['detections'], algorithm_config=algo_config
+            )
 
             # 将标注后的图片转换为 base64
             _, buffer = cv2.imencode('.jpg', annotated_frame)
@@ -47,7 +77,9 @@ async def detect_image(
                 data={
                     "detections": result['detections'],
                     "image_base64": img_base64,
-                    "stats": result['stats']
+                    "stats": result['stats'],
+                    "alerts": result.get('alerts', []),
+                    "behavior_stats": result.get('behavior_stats', {})
                 }
             )
         else:
@@ -64,3 +96,66 @@ async def detect_image(
             message=f"检测失败: {str(e)}",
             data={}
         )
+
+
+@router.get("/algorithms/config")
+async def get_algorithm_config():
+    """获取算法配置选项"""
+    return {
+        "algorithms": [
+            {
+                "id": "stationary_detection",
+                "name": "静止检测",
+                "description": "检测人员在同一位置静止停留",
+                "params": [
+                    {
+                        "name": "stationary_threshold",
+                        "label": "静止阈值",
+                        "type": "number",
+                        "default": 10.0,
+                        "min": 1.0,
+                        "max": 300.0,
+                        "unit": "秒",
+                        "description": "超过此时间视为静止"
+                    },
+                    {
+                        "name": "position_tolerance",
+                        "label": "位置容差",
+                        "type": "number",
+                        "default": 50,
+                        "min": 10,
+                        "max": 200,
+                        "unit": "像素",
+                        "description": "位置匹配容差范围"
+                    }
+                ]
+            },
+            {
+                "id": "loitering_detection",
+                "name": "徘徊检测",
+                "description": "检测人员长时间停留（需要跟踪ID）",
+                "params": [
+                    {
+                        "name": "loitering_threshold",
+                        "label": "徘徊阈值",
+                        "type": "number",
+                        "default": 300.0,
+                        "min": 60.0,
+                        "max": 1800.0,
+                        "unit": "秒",
+                        "description": "超过此时间视为徘徊"
+                    },
+                    {
+                        "name": "movement_threshold",
+                        "label": "移动阈值",
+                        "type": "number",
+                        "default": 5.0,
+                        "min": 1.0,
+                        "max": 50.0,
+                        "unit": "像素",
+                        "description": "小于此移动视为静止"
+                    }
+                ]
+            }
+        ]
+    }