Parking Available Slots Detection

A computer vision project that uses machine learning to detect and classify available parking slots in real-time. This project helps drivers find available parking spaces quickly and efficiently.

🚀 Features

• Real-time parking slot detection
• Machine learning-based classification of available/occupied slots
• Video processing capabilities
• Mask-based region of interest detection
• Support for high-resolution video input (1920x1080)

📋 Prerequisites

• Python 3.x
• OpenCV
• NumPy
• Jupyter Notebook (for running the demo)

🛠️ Installation

1. Clone the repository:

git clone https://github.com/Yossefmohammed/Parking-availiable-slots.git
cd Parking-availiable-slots

2. Install the required dependencies:

pip install opencv-python numpy jupyter

💻 Usage

1. Open the Jupyter notebook:

jupyter notebook check_slots.ipynb

2. Run the cells in the notebook to:
   • Load the pre-trained model
   • Process video input
   • Detect available parking slots
   • View real-time results

📁 Project Structure

• check_slots.ipynb - Main Jupyter notebook containing the implementation
• model.p - Pre-trained model for slot classification
• parking_1920_1080.mp4 - Sample video for testing
• mask_1920_1080.png - Mask file for defining regions of interest
• Screen Recording 2025-05-07 182016.mp4 - Demo video of the system in action

🤝 Contributing

Contributions, issues, and feature requests are welcome! Feel free to check the issues page.

📝 License

This project is open source and available under the MIT License.

👤 Author

Youssef Mohammed

• GitHub: @Yossefmohammed
• Email: [email protected]

🙏 Acknowledgments

• Thanks to all contributors who have helped shape this project
• Special thanks to the computer vision and machine learning community for their valuable resources and insights