🅿️ Real-Time Parking Slot Detection

A real-time smart parking system that uses Computer Vision and a custom-trained SVC classifier to detect and count available vs. occupied parking slots from video feeds.

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🚀 Features

• 🟣 Real-time video processing using OpenCV
• 🟣 Slot segmentation using a binary mask
• 🟣 Occupancy detection with a trained SVC classifier
• 🟣 Visual display of available vs. total slots
• 🟣 Scalable design for smart cities, malls, or surveillance drones

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🧠 Tech Stack

• Python 🐍
• OpenCV
• NumPy
• Scikit-learn (SVC Classifier)
• Skimage
• Matplotlib

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🗂️ Project Structure

├── Data/ # Contains parking lot video and mask images
├── Train classifier/ # Classifier training scripts & saved models
├── main.py # Main pipeline for real-time detection
├── utils.py # Helper functions (slot detection, classifier interface)
├── requirements.txt # Python dependencies

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⚙️ How to Run

1. Clone the repository:

   git clone https://github.com/ayyash1/parking-slot-detector.git
   cd parking-slot-detector

2. Install dependencies:

   pip install -r requirements.txt

3. Prepare your input video and mask:

   • Add your video to Data/
   • Use a binary mask image (PNG) to mark parking slot regions

4. Run detection:

   python main.py

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📈 Future Scope

• Mobile dashboard integration
• YOLOv8 or hybrid detection
• Edge device deployment
• IoT display for slot guidance

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🙍‍♂️Author

Developed by Ayyash Fous

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📄 License

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