The Parking Detection System is an application that uses computer vision techniques to detect and monitor parking spaces in real-time. The system analyzes video feeds from parking areas to determine which spots are occupied and which are available. This information can be used for:
- Real-time parking availability monitoring
- Parking usage analytics
- Smart parking management
- Automated parking guidance systems
The detection is based on image processing and machine learning algorithms that can identify vehicles in designated parking spaces and track changes in their occupancy status.
- Python 3.6+
- OpenCV
- NumPy
- TensorFlow or PyTorch (depending on the implementation)
- CUDA toolkit (optional, for GPU acceleration)
- Webcam or video input source
git clone https://github.com/yourusername/Parking-detection.git
cd Parking-detectionpython -m venv venv
source venv/bin/activate # On Windows, use `venv\Scripts\activate`pip install -r requirements.txtEdit the configuration file config.json to specify your video input source:
{
"input_source": "camera", // Options: "camera", "video_file", "rtsp"
"camera_id": 0, // Camera device ID (if using camera)
"video_path": "videos/parking_lot.mp4", // Path to video file (if using video_file)
"rtsp_url": "rtsp://example.com/stream" // RTSP URL (if using rtsp)
}Run the setup utility to define parking spaces:
python setup_parking_spaces.pyFollow the on-screen instructions to:
- Select points to define each parking space
- Save the parking space coordinates
python detect_parking.pyThe system will:
- Initialize the video input source
- Load the defined parking spaces
- Process each frame to detect parked vehicles
- Display results in real-time with occupied/available status for each space
To view parking usage analytics:
python generate_analytics.pyThis will produce reports and visualizations of parking space usage over time.
- Error: Cannot open camera/video file: Verify your input source configuration
- Poor detection accuracy: Try adjusting the detection parameters in
config.json - Performance issues: Consider enabling GPU acceleration or reducing input resolution
Contributions to improve the system are welcome. Please follow these steps:
- Fork the repository
- Create a feature branch
- Make your changes
- Submit a pull request
This project is licensed under the MIT License - see the LICENSE file for details.