CCTV智能检测系统 - 基于YOLOv8的对象检测与警报系统
Project description
CCTV 智能检测系统
基于 YOLOv8 的对象检测与警报系统,专为货舱监控设计。
功能特点
- 对象检测:支持人员、船只、机械等目标检测
- 货舱覆盖状态检测:已覆盖/部分覆盖/未覆盖
- 智能警报:自动检测并报警可疑情况
- 摄像头异常检测
- Web界面:友好的可视化界面
- JSON输出:标准化的检测结果输出
安装方法
pip install -e .
使用方法
1. 作为Python包使用
from cctv_detector import DetectionProcessor
# 创建检测器
detector = DetectionProcessor(
model_path="models/segment_best228.pt",
conf=0.25,
iou=0.45,
device="cuda"
)
# 处理图像
result = detector.process_image("test.jpg")
print(result)
2. 运行Web应用
from cctv_detector import run_webapp
# 运行Web应用
run_webapp(model_path="models/segment_best228.pt")
目录结构
cctv_detector/
├── src/
│ └── cctv_detector/
│ ├── __init__.py
│ ├── detector.py # 检测器核心模块
│ ├── visualizer.py # 可视化模块
│ └── webapp.py # Web应用模块
├── examples/
│ ├── run_detection.py # 检测示例
│ └── run_webapp.py # Web应用示例
├── models/
│ └── segment_best228.pt # 预训练模型
└── setup.py # 包配置文件
依赖要求
- Python >= 3.7
- PyTorch >= 1.9.0
- Ultralytics >= 8.0.0
- OpenCV >= 4.5.0
- Streamlit == 1.24.0
- 其他依赖见 setup.py
注意事项
- 首次运行前请确保已安装所有依赖
- 使用GPU加速需要安装CUDA支持的PyTorch版本
- 模型文件需要放在正确的位置
许可证
MIT License
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