Real-Time Face Attendance System

Overview

This project implements a real-time face attendance system integrated with a backend database. The system allows for the automatic recognition of students' faces during attendance sessions and updates the database in real-time with pertinent information such as ID number, student name, and last attendance time.

Features

• Real-time face recognition for attendance tracking.
• Integration with a real-time database to store student information.
• Automatic updating of the database with attendance records.
• Easy-to-use interface for administrators to manage attendance data.

Tools Used

• OpenCV: Utilized for real-time face detection and recognition.
• dlib: Used for its facial recognition capabilities.
• face_recognition: A high-level face recognition library built on top of dlib.
• cmake: A cross-platform tool for building, testing, and packaging software.
• Firebase: Integrated for real-time database functionality.
• cvzone: A computer vision library built on top of OpenCV for easy implementation of advanced vision tasks.

Installation

Install required dependencies:

pip install -r requirements.txt

Usage

1. Ensure that your environment meets the hardware requirements for real-time face recognition (e.g., a webcam).
2. Run the main application:

   python main.py
   

Configuration

• Modify the database connection settings in main.py and env file to match your environment.
• Adjust face recognition parameters in config.py for optimal performance.

Contributing

Contributions are welcome! If you'd like to contribute to this project, please follow these steps:

1. Fork the repository.
2. Create a new branch (git checkout -b feature/new-feature).
3. Make your changes.
4. Commit your changes (git commit -am 'Add new feature').
5. Push to the branch (git push origin feature/new-feature).
6. Create a new Pull Request.
7. [email protected]

Debugging outputs