8fb58c75fe
Features: - Fire detection (YOLOv10) - Helmet detection (YOLOv8) - Crowd detection (YOLOv8) - Smoking detection (YOLOv8) - Loitering detection (YOLOv8) Tech Stack: - Frontend: Vue 3 + Vite + Element Plus - Backend: FastAPI + WebSocket - Monorepo: pnpm workspace + Turbo - Docker support included
116 lines
4.5 KiB
Python
116 lines
4.5 KiB
Python
import os
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import logging
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from ultralytics import YOLO
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from typing import Dict, List, Optional
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logger = logging.getLogger(__name__)
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class ModelService:
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def __init__(self):
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self.models: Dict[str, YOLO] = {}
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# 基础路径：从 apps/server/services/model_service.py 到 jc-video-web 根目录
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base_dir = os.path.dirname(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
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self.model_configs = {
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'fire_detection': {
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'path': os.path.join(base_dir, 'models', 'fire_detection', 'best.pt'),
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'type': 'yolov10',
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'classes': ['Fire', 'Smoke'],
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'labels': {'Fire': '火焰', 'Smoke': '烟雾'},
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'size': '61MB',
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'description': '基于YOLOv10的火灾烟雾检测模型',
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'name': '火灾检测'
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},
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'helmet_detection': {
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'path': os.path.join(base_dir, 'models', 'helmet_detection', 'yolov8n.pt'),
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'type': 'yolov8',
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'classes': ['person', 'helmet'],
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'labels': {'person': '人员', 'helmet': '安全帽'},
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'size': '6MB',
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'description': '基于YOLOv8的安全帽检测模型',
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'name': '安全帽检测'
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},
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'crowd_detection': {
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'path': os.path.join(base_dir, 'models', 'crowd_detection', 'yolov8l.pt'),
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'type': 'yolov8',
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'classes': ['person'],
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'labels': {'person': '人员'},
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'size': '100MB',
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'description': '基于YOLOv8的人群聚集检测模型',
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'name': '人群检测'
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},
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'smoking_detection': {
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'path': os.path.join(base_dir, 'models', 'smoking_detection', 'smoking_yolov8n.pt'),
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'type': 'yolov8',
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'classes': ['cigarette', 'smoke'],
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'labels': {'cigarette': '香烟', 'smoke': '烟雾'},
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'size': '6MB',
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'description': '基于YOLOv8的抽烟检测模型',
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'name': '抽烟检测'
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},
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'loitering_detection': {
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'path': os.path.join(base_dir, 'models', 'loitering_detection', 'yolov8n.pt'),
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'type': 'yolov8',
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'classes': ['person'],
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'labels': {'person': '人员'},
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'size': '6MB',
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'description': '基于YOLOv8的徘徊检测模型',
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'name': '徘徊检测'
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}
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}
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def get_available_models(self) -> List[Dict]:
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available_models = []
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for model_id, config in self.model_configs.items():
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if os.path.exists(config['path']):
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available_models.append({
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'id': model_id,
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'name': config['name'],
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'description': config['description'],
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'classes': config['classes'],
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'labels': config['labels'],
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'size': config['size'],
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'type': config['type']
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})
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else:
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logger.warning(f"模型文件不存在: {config['path']}")
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return available_models
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async def load_model(self, model_id: str) -> Optional[YOLO]:
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if model_id not in self.model_configs:
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logger.error(f"未知模型ID: {model_id}")
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return None
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if model_id in self.models:
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logger.info(f"模型已加载: {model_id}")
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return self.models[model_id]
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config = self.model_configs[model_id]
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# 处理 YOLO 模型
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model_path = config['path']
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if not os.path.exists(model_path):
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logger.error(f"模型文件不存在: {model_path}")
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return None
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try:
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logger.info(f"正在加载模型: {model_id} from {model_path}")
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model = YOLO(model_path)
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self.models[model_id] = model
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logger.info(f"模型加载成功: {model_id}")
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return model
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except Exception as e:
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logger.error(f"模型加载失败: {model_id}, 错误: {e}")
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return None
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def get_model(self, model_id: str) -> Optional[YOLO]:
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return self.models.get(model_id)
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async def unload_model(self, model_id: str) -> bool:
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if model_id in self.models:
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del self.models[model_id]
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logger.info(f"模型已卸载: {model_id}")
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return True
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return False
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