SafeScan - AI-Powered COVID-19 Detection

📌 Overview

SafeScan is an AI-powered web application designed to detect COVID-19 using X-ray images. By leveraging deep learning techniques, it offers fast, accurate, and accessible diagnosis, reducing reliance on traditional PCR and antigen tests.

🔥 Features

• ✅ AI-driven COVID-19 detection from X-ray images
• ✅ Web-based interface for easy access
• ✅ MobileNet deep learning model for high accuracy
• ✅ Cloud deployment with Heroku & AWS S3
• ✅ Supports real-time image analysis

🛠️ Technologies Used

• Frontend: HTML, CSS, JavaScript
• Backend: Flask (Python)
• Model Architecture: MobileNet
• Database: AWS S3 for model storage
• Deployment: Heroku, GitHub Actions (CI/CD)

🚀 How It Works

1. Users upload an X-ray image via the web interface
2. The image is processed using a deep learning model
3. The system predicts if the image indicates COVID-19
4. Results are displayed instantly with confidence scores

⚙️ Installation & Setup

Follow these steps to set up the project locally:

1️⃣ Clone the Repository

git clone https://github.com/Amirbeek/COVID-19-Detector-Web-Application.git
cd SafeScan

2️⃣ Install Dependencies

pip install -r requirements.txt

3️⃣ Run the Application

python app.py

The web application will be available at http://127.0.0.1:5000/

📂 Project Structure

SafeScan/
│── static/            # Static assets (CSS, JS, images)
│── templates/         # HTML templates
│── models/           # Trained AI models
│── app.py            # Flask application
│── requirements.txt  # Dependencies
└── README.md         # Project documentation

📜 License

This project is licensed under the MIT License.

🤝 Acknowledgements

Special thanks to Brunel University London and my supervisor Webio Liu for their guidance and support throughout this project.

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🚀 Contributions are welcome! Feel free to fork this repository and submit a pull request. Let's make AI-powered diagnostics more accessible! 🌍