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_recognition Python 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-Recognition

python -m venv venv
source venv/bin/activate  # For Linux/macOS
venv\Scripts\activate     # For Windows

pip install -r requirements.txt

python manage.py makemigrations
python manage.py migrate

python manage.py runserver

Visit http://127.0.0.1:8000/ to get started!

if logged in as admin

after successfully filling the form

if logged in as authenticator

📷 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 📧 [email protected]