YOLOv11 Zone Intrusion Detection System

A computer vision-based intrusion detection system that uses YOLOv11 object detection and implements zone-based alerting for security monitoring.

Features

• Region of Interest (ROI) Detection: Optimized object detection that only processes within user-defined zones
• Multiple Detection Methods: YOLOv11 object detection with motion detection fallback
• Real-time Tracking: Tracks objects across video frames with unique IDs
• Zone-based Intrusion Alerts: Define restricted zones and get alerts when objects enter
• Logging & Reporting: CSV and YAML logging of intrusion events with timestamps
• Automatic Screenshots: Captures images when intrusions are detected
• Interactive UI: Real-time visualization with status information

Project Structure

motion_detection/
├── detect.py             # Main entry point
├── requirements.txt      # Project dependencies
├── lib/                  # Module library
│   ├── core/             # Core functionality
│   │   ├── intrusion_detector.py
│   │   └── zone_manager.py
│   ├── detectors/        # Detection algorithms
│   │   ├── yolo_detector.py
│   │   └── motion_detector.py
│   ├── trackers/         # Object tracking
│   │   └── simple_tracker.py
│   ├── ui/               # Visualization
│   │   └── visualizer.py
│   └── utils/            # Utilities
│       ├── config.py
│       └── logger.py
├── models/               # YOLO model files
├── logs/                 # Application logs
└── intrusions/           # Saved intrusion images

Installation

1. Clone the repository

   git clone [email protected]:zg0ul/motion-detection.git
   cd motion-detection
   

2. Set up a Python virtual environment (recommended)

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate
   

3. Install dependencies

   pip install -r requirements.txt
   

Requirements

Main dependencies include:

• OpenCV (cv2)
• Ultralytics (YOLO)
• NumPy
• Shapely (for polygon operations)
• PyYAML (for configuration)

Usage

Basic Usage

Run the detector with default settings (using webcam):

python detect.py

Command Line Options

python detect.py --source <VIDEO_SOURCE> --config <CONFIG_PATH> --model <MODEL_PATH>

• --source: Video source (0 for webcam, or path to video file)
• --config: Path to configuration file (optional)
• --model: Path to YOLOv11 model file (default: models/yolo11n.pt)

Interactive Controls

During operation, the following keyboard controls are available:

• q or ESC: Quit the application
• d: Toggle between YOLO detection and motion detection
• r: Reset background model (for motion detection)
• s: Save current configuration to file

Zone Definition

When you first run the application (or if no zone is defined):

1. You'll enter zone definition mode
2. Use left-clicks to place points defining your restricted zone
3. Right-click to complete the zone definition
4. Press q to save and continue

Contributing

Contributions are welcome! Please follow these steps:

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Make your changes
4. Commit your changes (git commit -m 'Add some amazing feature')
5. Push to the branch (git push origin feature/amazing-feature)
6. Open a Pull Request