The Face Recognition-Based Attendance System is a Python-based project designed to automate the attendance process using facial recognition technology. It leverages powerful libraries and tools to ensure accuracy and efficiency.
- 📸 Face Detection & Recognition: Real-time recognition using OpenCV and trained models.
- 📅 Attendance Management: Records attendance in a structured database.
- 🔒 Secure Storage: Data stored securely in MySQL.
- 📊 Analytics: Provides attendance reports and insights.
- Frontend: Tkinter for GUI
- Backend: Flask (Optional for web access), OpenCV, MySQL
- Database: MySQL
- Install Python (>= 3.7).
- Install the required libraries by running:
pip install -r requirements.txt
- Clone the repository:
git clone https://github.com/Wani-Chetan-999/FaceRecognitionAttendance.git
- Navigate to the project directory:
cd QuickAttend - Run the main Python script:
python login.py
Here are some screenshots of the system in action:
- Login Screen
- Registration Screen
- Main Window
- Student Registartion Pannel
- Data Train Module
- Face Detect & Mark Attendance
- Attedance Module
- Admin uploads user photos to register faces in the system.
- Users log their attendance by standing in front of the camera. The system will automatically detect and recognize their faces.
- Attendance records are automatically stored in the database.
- Admin can view or export attendance records as needed.
The system allows efficient and automatic attendance logging using face recognition, ensuring accuracy and ease of use.
Contributions are welcome! If you'd like to contribute, please follow these steps:
-
Fork the repository.
-
Create a new branch:
git checkout -b feature/YourFeature
-
Commit your changes:
git commit -m 'Add some feature' -
Push to the branch:
git push origin feature/YourFeature
-
Open a Pull Request
For any inquiries or support, feel free to reach out:
- Name: Chetan Wani
- GitHub: Wani-Chetan-999
- Contact: 8275540085
- Email: 02ckwani@gmail.com