🎓 Classroom Attendance Tracker with Computer Vision

Welcome to the Classroom Attendance Tracker! This is a full-stack web application hosted on Firebase that uses Firebase Authentication and Firebase Realtime Database for secure CRUD operations. The app leverages TensorFlow.js for real-time computer vision, enabling automatic attendance marking through facial recognition.

🚀 Features

• User Authentication: Secure login and registration using Firebase Authentication.
• Realtime Database: Store and retrieve attendance records instantly.
• Computer Vision: Facial recognition powered by TensorFlow.js for attendance marking.
• Cross-Platform: Works on modern web browsers without additional installations.
• CRUD Operations: Manage student records with create, read, update, and delete functionality.

🛠️ Tech Stack

• Frontend: HTML, CSS, JavaScript
• Backend: Firebase Realtime Database
• Authentication: Firebase Authentication
• Machine Learning: TensorFlow.js
• Hosting: Firebase Hosting

📸 How It Works

• User Login: Authenticate using Firebase Authentication.
• Student Management: Add student records through the web interface.
• Face Detection: The app uses TensorFlow.js to detect faces using the device camera.
• Attendance Marking: Recognized students are automatically marked as present in the Firebase database.

🚨 Security Considerations

• Data Security: All user data is securely stored in Firebase Realtime Database.
• Authentication: Firebase Authentication ensures only authorized users access the platform.
• Privacy: Face data is processed locally in the browser using TensorFlow.js, ensuring privacy.

⚠️⚠️⚠️ CURRENTLY NOT WORKING ⚠️⚠️⚠️