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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

  1. 首次运行前请确保已安装所有依赖
  2. 使用GPU加速需要安装CUDA支持的PyTorch版本
  3. 模型文件需要放在正确的位置

许可证

MIT License

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