🚀 Topic: Building a student identity authentication system using facial recognition in testing

🌟 Introduction

The topic is to build a student identity authentication system based on facial recognition technology for testing (at Phenikaa University) to ensure accuracy, transparency and safety in exams

Demo, Report and Slide:

• Report end

• Demo

• Report

• Video demo

• Video demo RestfulAPT

• Presentation

Author

Nguyen Duc Anh	Instructor: TS. Nguyen Le Thu

Framework

Express + NodeJS	Refine	React + TypeScript + Vite

Deployment Platforms (With Free Tier)

Vercel	Render	Aiven	Redis

🛠️ Architecture

Client-Server Architecture - System Design

• Knex
• JWT

🛠️ Prerequisites

Before you start, make sure you have the following prerequisites installed on your system:

• NodeJS (version 20.18.0 or higher)
• MySQL (or any other supported database system)
• Python (version 3.12.0 or higher)
• opencv_python (version 4.10.0.84 or higher)
• dlib (here I got an error when trying pip install dlib, if you get an access error Dlib_Windows_Python3.x to install manually following the instructions)
• insightface (used as the primary face recognition library)
• face-recognition (version 1.3.0 or higher)
• Silent-Face-Anti-Spoofing (author: minivision-ai)

🔧 Step-by-step installation

Step 1: 🚀 Install NodeJS

• Make sure NodeJS is installed. You can check their version with the following commands:

node -v

Step 2: 📁 After installing NodeJS, you can download the project:

git clone https://github.com/anhhducnguyen/Face-Auth-Exam-System-v2.git

Step 3: ⚙️ Reconfigure the .env file according to the following information

• If you want to use MySQL, update the DB_* variables in the server\.env configuration file as follows:

  DB_HOST=localhost
  DB_USER=root
  DB_PASSWORD=your_db_password
  DB_NAME=exammanagement_do_an
  
  TOKEN_SECRET=your_token_secret
  
  EMAIL_USER[email protected]	
  EMAIL_PASS=your_email_password
  
  GOOGLE_CLIENT_ID=your_google_client_id
  GOOGLE_CLIENT_SECRET=your_google_client_secret
  GOOGLE_CALLBACK_URL=http://localhost:5000/auth/google/callback
  
  SESSION_SECRET=your_session_secret
  JWT_SECRET=your_jwt_secret

Step 4: Create the database

Step 5: 🏃‍♂️ Once the project has been created

cd Face-Auth-Exam-System-v2

cd server
npm install
npm run dev 

cd admin
npm install
npm run dev 

cd client
npm install
npm run dev 

cd Silent-Face-Anti-Spoofing
pip install -r requirements.txt
python main.py

See details at our Issue

📄 License

This project is licensed under the GNU General Public License v3.0.

© 2025 Nguyen Duc Anh