ROI选区01

config.py

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+import os
+from pathlib import Path
+from typing import Any, Dict, List, Optional
+
+import yaml
+from pydantic import BaseModel, Field
+
+
+class DatabaseConfig(BaseModel):
+    dialect: str = "sqlite"
+    host: str = "localhost"
+    port: int = 3306
+    username: str = "root"
+    password: str = "password"
+    name: str = "security_monitor"
+    echo: bool = False
+
+    @property
+    def url(self) -> str:
+        if self.dialect == "sqlite":
+            return f"sqlite:///{self.name}.db"
+        return f"mysql+pymysql://{self.username}:{self.password}@{self.host}:{self.port}/{self.name}"
+
+
+class ModelConfig(BaseModel):
+    engine_path: str = "models/yolo11n_fp16_480.engine"
+    pt_model_path: str = "models/yolo11n.pt"
+    imgsz: List[int] = [480, 480]
+    conf_threshold: float = 0.5
+    iou_threshold: float = 0.45
+    device: int = 0
+    batch_size: int = 8
+    half: bool = True
+
+
+class StreamConfig(BaseModel):
+    buffer_size: int = 2
+    reconnect_delay: float = 3.0
+    timeout: float = 10.0
+    fps_limit: int = 30
+
+
+class InferenceConfig(BaseModel):
+    queue_maxlen: int = 100
+    event_queue_maxlen: int = 1000
+    worker_threads: int = 4
+
+
+class AlertConfig(BaseModel):
+    snapshot_path: str = "data/alerts"
+    cooldown_sec: int = 300
+    image_quality: int = 85
+
+
+class ROIConfig(BaseModel):
+    default_types: List[str] = ["polygon", "line"]
+    max_points: int = 50
+
+
+class WorkingHours(BaseModel):
+    start: List[int] = Field(default_factory=lambda: [8, 30])
+    end: List[int] = Field(default_factory=lambda: [17, 30])
+
+
+class AlgorithmsConfig(BaseModel):
+    leave_post_threshold_sec: int = 360
+    leave_post_confirm_sec: int = 30
+    leave_post_return_sec: int = 5
+    intrusion_check_interval_sec: float = 1.0
+    intrusion_direction_sensitive: bool = False
+
+
+class LoggingConfig(BaseModel):
+    level: str = "INFO"
+    format: str = "%(asctime)s - %(name)s - %(levelname)s - %(message)s"
+    file: str = "logs/app.log"
+    max_size: str = "100MB"
+    backup_count: int = 5
+
+
+class MonitoringConfig(BaseModel):
+    enabled: bool = True
+    port: int = 9090
+    path: str = "/metrics"
+
+
+class LLMConfig(BaseModel):
+    enabled: bool = False
+    api_key: str = ""
+    base_url: str = ""
+    model: str = "qwen-vl-max"
+    timeout: int = 30
+
+
+class Config(BaseModel):
+    database: DatabaseConfig = Field(default_factory=DatabaseConfig)
+    model: ModelConfig = Field(default_factory=ModelConfig)
+    stream: StreamConfig = Field(default_factory=StreamConfig)
+    inference: InferenceConfig = Field(default_factory=InferenceConfig)
+    alert: AlertConfig = Field(default_factory=AlertConfig)
+    roi: ROIConfig = Field(default_factory=ROIConfig)
+    working_hours: List[WorkingHours] = Field(default_factory=lambda: [
+        WorkingHours(start=[8, 30], end=[11, 0]),
+        WorkingHours(start=[12, 0], end=[17, 30])
+    ])
+    algorithms: AlgorithmsConfig = Field(default_factory=AlgorithmsConfig)
+    logging: LoggingConfig = Field(default_factory=LoggingConfig)
+    monitoring: MonitoringConfig = Field(default_factory=MonitoringConfig)
+    llm: LLMConfig = Field(default_factory=LLMConfig)
+
+
+_config: Optional[Config] = None
+
+
+def load_config(config_path: Optional[str] = None) -> Config:
+    """加载配置文件"""
+    global _config
+
+    if _config is not None:
+        return _config
+
+    if config_path is None:
+        config_path = os.environ.get(
+            "CONFIG_PATH",
+            str(Path(__file__).parent / "config.yaml")
+        )
+
+    if os.path.exists(config_path):
+        with open(config_path, "r", encoding="utf-8") as f:
+            yaml_config = yaml.safe_load(f) or {}
+    else:
+        yaml_config = {}
+
+    _config = Config(**yaml_config)
+    return _config
+
+
+def get_config() -> Config:
+    """获取配置单例"""
+    if _config is None:
+        return load_config()
+    return _config
+
+
+def reload_config(config_path: Optional[str] = None) -> Config:
+    """重新加载配置"""
+    global _config
+    _config = None
+    return load_config(config_path)