engin-smith / student-attendance-face-recognition

Facial Recognition: Utilizes deep learning algorithms to recognize and authenticate students based on their facial features.

Student AttendanceFace Recognition System

This project is a facial recognition-based attendance system designed for educational institutions. It automates the attendance process using advanced facial recognition technology, offering a more efficient and accurate alternative to traditional attendance tracking methods.

Key Features:

• Facial Recognition: Utilizes deep learning algorithms to recognize and authenticate students based on their facial features.
• Real-time Tracking: Captures and processes attendance data in real-time, providing instant updates to the attendance database.
• User-Friendly Interface: Offers an intuitive and easy-to-use interface for both administrators and students.
• Automated Reporting: Generates comprehensive attendance reports automatically, reducing manual work for administrators.
• Security: Ensures data privacy and security through encryption and access control mechanisms.
• Scalability: Designed to handle a large number of users and scale according to the institution's needs.
• Customization: Allows customization of attendance rules, notifications, and other settings as per institutional requirements.

Technologies Used

Python for backend development and machine learning models. OpenCV and Dlib for face detection and recognition. custome windows for building the application interface. firebase for database management. python for frontend development.

Installation

Clone the repository to your local machine.

  https://github.com/Engin-Smith/student-attendance-face-recognition.git

Install the necessary dependencies using

  install cmake
  install dlib
  install cvzone or openCV
  install face-recongintion 

Database

  fix the database with firebase 

Run the application using python3 main.py.

this application we're using windows form

Tech Stack

Client: Python

Server: FireBases

Screenshots

License

This project is licensed under the MIT License - see the LICENSE.md file for details.

Disclaimer

Please note that while this system aims to provide accurate attendance tracking, it may not be foolproof and may require human verification in certain cases. Use it responsibly and in compliance with legal and ethical standards.