A Django-based web application that enables secure and automated candidate registration and authentication using face recognition. This project aims to streamline the identity verification process for exams, interviews, or any environment requiring controlled access.
- 📷 Live Image Capture: Capture candidate's photo in real-time using webcam.
- 📝 Candidate Registration: Register candidates with name and roll number along with their facial image.
- 🧠 Face Recognition Authentication: Authenticate a person by comparing live camera feed with registered facial data.
- 🗃️ Admin Dashboard: View all registered candidates from the admin panel.
- 🔐 Secure Image Upload: Validates file format and handles media storage safely.
- Backend: Django 5.1.2
- Frontend: HTML, CSS (custom styling)
- Face Recognition:
face_recognitionPython library (built on dlib) - Database: SQLite (default) or extendable to PostgreSQL
- Media Handling: Django Media Files
git clone https://github.com/COREayan/Automated-Candidate-Authentication-System-using-Face-Recognition.git
cd Automated-Candidate-Authentication-System-using-Face-Recognitionpython -m venv venv
source venv/bin/activate # For Linux/macOS
venv\Scripts\activate # For Windowspip install -r requirements.txtpython manage.py makemigrations
python manage.py migratepython manage.py runserverVisit http://127.0.0.1:8000/ to get started!
after successfully filling the form

📷 Face Recognition Setup The system uses the face_recognition library to encode and compare faces. Make sure your webcam is connected. You may need to install additional system packages for dlib.
pip install face_recognition opencv-python✅ Usage Go to /image-request/ to register a candidate.
Visit /authenticate/ to authenticate a candidate using live face recognition.
Admin can access the database through /admin/.
🧑💻 Author Ayanabha Pramanik
📍 From West Bengal, India 🔗 LinkedIn 📧 ayanabha.pramanik.ee@gmail.com


