himaldahal / facial-attendance-system

Our facial attendance system automates attendance tracking using facial recognition technology. Built with Flask, Bootstrap 5, and OpenCV, it offers seamless integration with web interfaces and webcam-based data collection. Simplify attendance management with dataset gathering, model training, and real-time recognition.

👨‍💼 Facial Attendance System

This project is a facial attendance system that utilizes Flask for the backend, Bootstrap 5 for the frontend, and OpenCV for face detection and recognition.

Project Structure

📦 facial-attendance-system
├─ backend
│  ├─ app.py
│  ├─ instance
│  │  └─ face_recognition_db.sqlite
│  └─ templates
│     └─ index.html
├─ dataset.py
├─ face_recognizer.py
├─ haarcascade_frontalface_default.xml
├─ trainer.py
├─ trainer
│  └─ trainer.yml
└─ webcam_dataset.py

Features

• 🔧 Backend developed with Flask
• 🎨 Webpage styled using Bootstrap 5
• 👤 Facial detection and recognition using OpenCV
• 📸 Dataset gathering through webcam or images
• 📊 Model training for accurate recognition
• 📝 Attendance marking based on recognized faces

Usage

1. 📸 Run dataset.py to gather photos from a video or webcam_dataset.py to capture photos from a live camera feed for the dataset.
2. 🚀 Run trainer.py to train the model using the gathered dataset.
3. ⚙️ Ensure that the Flask server is running by executing python3 app.py.
4. 👀 Run face_recognizer.py to recognize faces and mark attendance.

To run the Flask server:

python3 app.py

Access the web interface at http://localhost:5000.

Installation

You can install the required packages using pip3. Run the following command:

pip3 install Flask opencv-python opencv-contrib-python requests

Contributing

🤝 Contributions are welcome! If you find any bugs or have suggestions for improvements, please open an issue or submit a pull request.

License

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