🚗 Vehicle Detection and Tracking

📌 Overview

This project is designed to detect and track vehicles in video footage using Computer Vision and Machine Learning techniques. It leverages TensorFlow Object Detection and Kalman Filters for accurate tracking.

🚀 Features

• 🔍 Vehicle Detection: Identifies vehicles in video streams.
• 📌 Object Tracking: Uses Kalman Filters for tracking movement.
• 🎥 Multiple Camera Support: Works with single or multiple video sources.
• ⚡ Real-time Processing: Processes video frames efficiently.
• 📈 Warning System: Alerts when vehicles enter restricted areas.

🛠️ Tech Stack

Language/Framework	Usage
	Core programming language
	Computer vision processing
	Numerical computations
	Object detection model
	Video processing

📂 Project Structure

📁 VehicleDetectionAndTracking
│-- 🚀 VehicleDetectionAndTracking.py
│-- 📹 OneCameraFront.py
│-- 📹 OneCameraRear.py
│-- 📹 TwoCamerasFront.py
│-- 📹 TwoVideoTrackingTest.py
│-- 📂 utilities
│   │-- 🚗 VehicleDetector.py
│   │-- 🚘 VehicleTracker.py
│-- 📄 LICENSE
│-- 📄 README.md
│-- 📄 .gitignore

▶️ How to Run

🔧 Prerequisites

Ensure you have Python installed. Install dependencies:

pip install numpy opencv-python moviepy tensorflow tqdm

🏁 Running the Project

1️⃣ Run Detection & Tracking on a Single Front Camera

python OneCameraFront.py

2️⃣ Run Detection & Tracking on a Single Rear Camera

python OneCameraRear.py

3️⃣ Run Detection on Two Front Cameras

python TwoCamerasFront.py

4️⃣ Test Vehicle Tracking with Synthetic Data

python TwoVideoTrackingTest.py

📜 License

This project is licensed under the MIT License. See the LICENSE file for details.

🤝 Contributing

Feel free to contribute! Fork the repository, make changes, and submit a pull request.

📧 Contact

For any inquiries, reach out via email or open an issue in the repository.

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🚀 Happy Coding! 🎯