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Security_AI_integrated/config.yaml
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fix(cache): 修复 _load_rois_from_db 未加载 working_hours 字段的问题
- 在 roi_config 中补充读取数据库中的 working_hours 字段
- 确保 pipeline 能将 ROI 特定的工作时间配置正确传递给算法
- 修复后,LeavePostAlgorithm.is_in_working_hours() 将使用 ROI 配置而非全局默认值
2026-01-22 18:26:57 +08:00

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# 安保异常行为识别系统 - 核心配置
# 云端同步配置
cloud:
enabled: false # 启用云端同步(云端为主、本地为辅)
api_url: "https://api.example.com" # 云端API地址
api_key: "your-api-key" # API密钥
device_id: "EDGE-001" # 设备唯一标识
sync_interval: 60 # 配置同步间隔(秒)
alarm_retry_interval: 60 # 报警重试间隔(秒)
status_report_interval: 60 # 状态上报间隔(秒)
max_retries: 3 # 最大重试次数
# 数据库配置
database:
dialect: "sqlite" # sqlite 或 mysql
host: "localhost"
port: 3306
username: "root"
password: "password"
name: "security_monitor"
echo: true # SQL日志输出
# TensorRT模型配置
model:
engine_path: "models/yolo11n.engine"
onnx_path: "models/yolo11n.onnx"
pt_model_path: "models/yolo11n.pt"
imgsz: [640, 640]
conf_threshold: 0.5
iou_threshold: 0.45
device: 0
batch_size: 8
half: false
use_onnx: true
# RTSP流配置
stream:
buffer_size: 2 # 每路摄像头帧缓冲大小
reconnect_delay: 3.0 # 重连延迟(秒)
timeout: 10.0 # 连接超时(秒)
fps_limit: 10.0 # 最大处理FPS
# 推理队列配置
inference:
queue_maxlen: 100 # 检测结果队列最大长度
event_queue_maxlen: 1000 # 异常事件队列最大长度
worker_threads: 4 # 处理线程数
# 告警配置
alert:
snapshot_path: "data/alerts"
cooldown_sec: 300 # 同类型告警冷却时间
image_quality: 85 # JPEG质量
# ROI配置
roi:
default_types:
- "polygon"
- "line"
max_points: 50 # 多边形最大顶点数
# 工作时间配置(全局默认,空数组表示全天开启)
working_hours: []
# 算法默认参数
algorithms:
leave_post:
threshold_sec: 300 # 离岗超时5分钟
confirm_sec: 10 # 上岗确认时间10秒
return_sec: 30 # 离岗缓冲时间30秒
intrusion:
cooldown_seconds: 300 # 入侵检测冷却时间(秒)
# 日志配置
logging:
level: "INFO"
format: "%(asctime)s - %(name)s - %(levelname)s - %(message)s"
file: "logs/app.log"
max_size: "100MB"
backup_count: 5
# 监控配置
monitoring:
enabled: true
port: 9090 # Prometheus metrics端口
path: "/metrics"
# 大模型配置(预留)
llm:
enabled: false
api_key: "sk-21e61bef09074682b589da3bdbfe07a2"
base_url: "https://dashscope.aliyuncs.com/compatible-mode/v1"
model: "qwen3-vl-max"
timeout: 30