16337
003c2885b9
- settings.py: 删除 80 类 COCO_CLASS_NAMES 硬编码，改为 MODEL_CLASS_NAMES
+ 新增 MODEL_NUM_CLASSES / MODEL_OUTPUT_CHANNELS 辅助常量
+ 新增 ALGO_INTENT_CLASSES 字典 + get_algo_target_classes() 辅助函数
+ COCO_CLASS_NAMES 保留名称向后兼容，指向 MODEL_CLASS_NAMES
- postprocessor.py: 4 处硬编码 84 → MODEL_OUTPUT_CHANNELS
+ 支持不同类别数模型切换不改代码
- algorithms.py: 4 处硬编码 target_classes 默认值 → get_algo_target_classes()
+ IllegalParkingAlgorithm / VehicleCongestionAlgorithm /
NonMotorVehicleParkingAlgorithm / GarbageDetectionAlgorithm
+ 自动过滤当前模型不支持的类（truck/bus 等）
以后换模型只需修改 settings.py 一处 MODEL_CLASS_NAMES。
381 lines
12 KiB
Python
381 lines
12 KiB
Python
"""
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全局配置模块
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定义数据库、Redis、MQTT、推理等各项配置参数
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"""
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import os
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from dataclasses import dataclass, field
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from typing import Dict, List, Optional
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@dataclass
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class DatabaseConfig:
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"""数据库配置类（MySQL - 云端）"""
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host: str = "localhost"
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port: int = 3306
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username: str = "root"
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password: str = ""
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database: str = "edge_inference"
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pool_size: int = 10
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pool_recycle: int = 3600
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echo: bool = False
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@dataclass
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class SQLiteConfig:
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"""SQLite 配置（边缘侧本地存储）"""
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db_path: str = "./data/security_events.db"
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image_dir: str = "./data/captures"
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retention_days: int = 7
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wal_mode: bool = True
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batch_size: int = 100
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flush_interval: float = 5.0
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@dataclass
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class RedisConfig:
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"""Redis配置类（本地 Redis，边缘侧缓存）"""
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host: str = "localhost"
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port: int = 6379
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db: int = 0
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password: Optional[str] = None
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decode_responses: bool = True
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max_connections: int = 50
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@dataclass
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class CloudRedisConfig:
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"""云端 Redis 配置（三层权威模型 - 云端层）"""
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host: str = "localhost"
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port: int = 6379
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db: int = 1
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password: Optional[str] = None
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decode_responses: bool = True
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max_connections: int = 20
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@dataclass
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class LocalRedisConfig:
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"""本地 Redis 配置（三层权威模型 - 边缘层缓存）"""
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host: str = "localhost"
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port: int = 6379
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db: int = 1
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password: Optional[str] = None
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decode_responses: bool = True
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max_connections: int = 20
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@dataclass
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class MQTTConfig:
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"""MQTT配置类（保留配置结构，不再用于告警上报）"""
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broker_host: str = "localhost"
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broker_port: int = 1883
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client_id: str = "edge_inference_service"
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device_id: str = "default"
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username: Optional[str] = None
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password: Optional[str] = None
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keepalive: int = 60
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qos: int = 1
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reconnect_delay: int = 5
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max_reconnect_attempts: int = 10
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@dataclass
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class COSConfig:
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"""腾讯云 COS 配置"""
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secret_id: str = ""
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secret_key: str = ""
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region: str = "ap-beijing"
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bucket: str = ""
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@dataclass
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class AlarmUploadConfig:
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"""告警上报配置"""
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cloud_api_url: str = "http://localhost:8000"
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wvp_api_url: str = "" # WVP 平台地址（心跳同步用）
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edge_token: str = ""
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retry_max: int = 3
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retry_interval: int = 5
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@dataclass
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class VideoStreamConfig:
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"""视频流配置类"""
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default_fps: int = 5
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reconnect_max_attempts: int = 5
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reconnect_base_delay: float = 1.0
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reconnect_max_delay: float = 60.0
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frame_buffer_size: int = 30
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connection_timeout: int = 10
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read_timeout: int = 30
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@dataclass
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class InferenceConfig:
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"""推理配置类"""
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model_path: str = "./models/yolo11n.engine"
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input_width: int = 480
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input_height: int = 480
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batch_size: int = 1
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conf_threshold: float = 0.45
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nms_threshold: float = 0.5
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device_id: int = 0
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fp16_mode: bool = True
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# 按算法类型覆盖置信度阈值，key=algo_code, value=threshold
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# 未命中时回退到 conf_threshold
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algo_conf_thresholds: Dict[str, float] = field(default_factory=dict)
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def get_conf_threshold(self, algo_code: str) -> float:
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"""获取指定算法的置信度阈值，未配置则回退全局值"""
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return self.algo_conf_thresholds.get(algo_code, self.conf_threshold)
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# ===================== Debug / Local Sync =====================
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@dataclass
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class DebugConfig:
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"""本地调试相关配置"""
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enabled: bool = True
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host: str = "127.0.0.1"
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port: int = 9001
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reload_signal_file: str = "./config/reload.signal"
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local_config_path: str = "./config/local_config.json"
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# 模型类别配置（支持不同模型切换，修改此处即可）
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# 当前: yolo11s_v2plus_20260421 (5 类定制模型)
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# 历史: yolo11n 官方 (80 类 COCO)，列表见 git 历史
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MODEL_CLASS_NAMES = ["garbage", "person", "car", "bicycle", "motorcycle"]
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MODEL_NUM_CLASSES = len(MODEL_CLASS_NAMES) # 模型类别数
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MODEL_OUTPUT_CHANNELS = 4 + MODEL_NUM_CLASSES # YOLO 输出通道 = 4(xywh) + nc
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# 向后兼容：保留 COCO_CLASS_NAMES 名称，指向当前模型类别
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COCO_CLASS_NAMES = MODEL_CLASS_NAMES
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# 各算法的业务关注类别（全集，不限定当前模型是否支持）
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# 部署时通过 get_algo_target_classes() 自动过滤出当前模型支持的子集
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ALGO_INTENT_CLASSES = {
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"leave_post": ["person"],
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"intrusion": ["person"],
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"illegal_parking": ["car", "truck", "bus"],
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"vehicle_congestion": ["car", "truck", "bus", "motorcycle"],
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"non_motor_vehicle_parking": ["bicycle", "motorcycle"],
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"garbage": ["garbage"],
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}
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def get_algo_target_classes(algo_code: str) -> list:
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"""获取算法的目标类别，自动过滤出当前模型支持的类
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Args:
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algo_code: 算法代码 (leave_post / intrusion / illegal_parking / ...)
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Returns:
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目标类名列表，保证每个类都在 MODEL_CLASS_NAMES 中
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"""
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intent = ALGO_INTENT_CLASSES.get(algo_code, [])
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return [c for c in intent if c in MODEL_CLASS_NAMES]
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@dataclass
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class CameraConfig:
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"""单个摄像头配置"""
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camera_id: str
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rtsp_url: str
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enabled: bool = True
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roi_ids: List[str] = field(default_factory=list)
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@dataclass
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class ROIConfig:
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"""ROI区域配置"""
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roi_id: str
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camera_id: str
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roi_type: str # 'polygon' or 'rectangle'
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coordinates: List[List[float]] # 多边形顶点或矩形坐标
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algorithm_type: str # 'leave_post', 'intrusion', etc.
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alert_threshold: int = 3 # 连续N帧触发告警
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alert_cooldown: int = 300 # 告警冷却时间(秒)
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class Settings:
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"""全局设置单例类"""
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_instance = None
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_initialized = False
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def __new__(cls):
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if cls._instance is None:
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cls._instance = super().__new__(cls)
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return cls._instance
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def __init__(self):
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if not self._initialized:
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self._load_env_vars()
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self._initialized = True
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def _load_env_vars(self):
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"""从环境变量加载配置"""
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# 加载 .env 文件（如果 python-dotenv 可用）
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try:
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from dotenv import load_dotenv
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load_dotenv()
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except ImportError:
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pass
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base_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
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def _abs_path(path: str) -> str:
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if not path:
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return path
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return path if os.path.isabs(path) else os.path.normpath(os.path.join(base_dir, path))
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self.database = DatabaseConfig(
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host=os.getenv("DB_HOST", "localhost"),
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port=int(os.getenv("DB_PORT", "3306")),
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username=os.getenv("DB_USERNAME", "root"),
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password=os.getenv("DB_PASSWORD", ""),
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database=os.getenv("DB_DATABASE", "edge_inference"),
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)
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self.sqlite = SQLiteConfig(
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db_path=_abs_path(os.getenv("SQLITE_DB_PATH", "./data/security_events.db")),
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image_dir=_abs_path(os.getenv("SQLITE_IMAGE_DIR", "./data/captures")),
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retention_days=int(os.getenv("SQLITE_RETENTION_DAYS", "7")),
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wal_mode=os.getenv("SQLITE_WAL_MODE", "1") == "1",
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)
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self.redis = RedisConfig(
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host=os.getenv("REDIS_HOST", "localhost"),
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port=int(os.getenv("REDIS_PORT", "6379")),
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password=os.getenv("REDIS_PASSWORD"),
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)
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self.cloud_redis = CloudRedisConfig(
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host=os.getenv("CLOUD_REDIS_HOST", "localhost"),
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port=int(os.getenv("CLOUD_REDIS_PORT", "6379")),
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db=int(os.getenv("CLOUD_REDIS_DB", "1")),
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password=os.getenv("CLOUD_REDIS_PASSWORD"),
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)
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self.local_redis = LocalRedisConfig(
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host=os.getenv("LOCAL_REDIS_HOST", "localhost"),
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port=int(os.getenv("LOCAL_REDIS_PORT", "6379")),
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db=int(os.getenv("LOCAL_REDIS_DB", "1")),
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password=os.getenv("LOCAL_REDIS_PASSWORD"),
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)
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self.mqtt = MQTTConfig(
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broker_host=os.getenv("MQTT_BROKER_HOST", "localhost"),
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broker_port=int(os.getenv("MQTT_BROKER_PORT", "1883")),
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client_id=os.getenv("MQTT_CLIENT_ID", "edge_inference_service"),
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device_id=os.getenv("EDGE_DEVICE_ID", "default"),
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username=os.getenv("MQTT_USERNAME"),
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password=os.getenv("MQTT_PASSWORD"),
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)
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self.cos = COSConfig(
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secret_id=os.getenv("COS_SECRET_ID", ""),
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secret_key=os.getenv("COS_SECRET_KEY", ""),
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region=os.getenv("COS_REGION", "ap-beijing"),
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bucket=os.getenv("COS_BUCKET", ""),
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)
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self.alarm_upload = AlarmUploadConfig(
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cloud_api_url=os.getenv("CLOUD_API_URL", "http://localhost:8000"),
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wvp_api_url=os.getenv("WVP_API_URL", ""),
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edge_token=os.getenv("EDGE_TOKEN", ""),
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retry_max=int(os.getenv("ALARM_RETRY_MAX", "3")),
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retry_interval=int(os.getenv("ALARM_RETRY_INTERVAL", "5")),
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)
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self.alarm_upload_enabled = os.getenv("ALARM_UPLOAD_ENABLED", "1") == "1"
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self.video_stream = VideoStreamConfig(
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default_fps=int(os.getenv("VIDEO_DEFAULT_FPS", "5")),
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reconnect_max_attempts=int(os.getenv("VIDEO_RECONNECT_ATTEMPTS", "5")),
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)
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self.inference = InferenceConfig(
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model_path=os.getenv("MODEL_PATH", "./models/yolo11n.engine"),
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input_width=int(os.getenv("INPUT_WIDTH", "480")),
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input_height=int(os.getenv("INPUT_HEIGHT", "480")),
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batch_size=int(os.getenv("BATCH_SIZE", "4")),
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conf_threshold=float(os.getenv("CONF_THRESHOLD", "0.45")),
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nms_threshold=float(os.getenv("NMS_THRESHOLD", "0.5")),
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algo_conf_thresholds=self._parse_algo_conf_thresholds(),
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)
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self.config_sync_mode = os.getenv("CONFIG_SYNC_MODE", "LOCAL").upper()
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self.debug = DebugConfig(
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enabled=os.getenv("DEBUG_SERVER_ENABLED", "1") == "1",
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host=os.getenv("DEBUG_SERVER_HOST", "127.0.0.1"),
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port=int(os.getenv("DEBUG_SERVER_PORT", "9001")),
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reload_signal_file=_abs_path(os.getenv("DEBUG_RELOAD_SIGNAL_FILE", "./config/reload.signal")),
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local_config_path=_abs_path(os.getenv("LOCAL_CONFIG_PATH", "./config/local_config.json")),
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)
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self.log_level = os.getenv("LOG_LEVEL", "INFO")
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self.log_dir = os.getenv("LOG_DIR", "./logs")
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self.log_file_max_size = int(os.getenv("LOG_FILE_MAX_SIZE", "10485760"))
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self.log_file_backup_count = int(os.getenv("LOG_FILE_BACKUP_COUNT", "5"))
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self.working_hours = self._parse_working_hours()
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# 使用 COCO 类别名称
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self.class_names = COCO_CLASS_NAMES
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@staticmethod
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def _parse_algo_conf_thresholds() -> Dict[str, float]:
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"""解析 ALGO_CONF_* 环境变量，返回 {algo_code: threshold} 字典
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环境变量命名规则: ALGO_CONF_{ALGO_CODE}，如:
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ALGO_CONF_LEAVE_POST=0.35
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ALGO_CONF_INTRUSION=0.55
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"""
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prefix = "ALGO_CONF_"
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result = {}
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for key, value in os.environ.items():
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if key.startswith(prefix) and value:
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algo_code = key[len(prefix):].lower()
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try:
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result[algo_code] = float(value)
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except ValueError:
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pass
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return result
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def _parse_working_hours(self) -> List[dict]:
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"""解析工作时间配置"""
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working_hours_str = os.getenv("WORKING_HOURS", "")
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if not working_hours_str:
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return []
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working_hours = []
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periods = working_hours_str.split(";")
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for period in periods:
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try:
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start, end = period.split("-")
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start_h, start_m = map(int, start.split(":"))
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end_h, end_m = map(int, end.split(":"))
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working_hours.append({
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"start": [start_h, start_m],
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"end": [end_h, end_m]
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})
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except (ValueError, AttributeError):
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continue
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return working_hours
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@property
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def config_version(self) -> str:
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"""获取配置版本号"""
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return os.getenv("CONFIG_VERSION", "1.0.0")
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def get_settings() -> Settings:
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"""获取全局配置单例"""
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return Settings()
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