Smart Attendance System

A web-based attendance management system using face recognition technology built with FastAPI and React.

Features

Authentication & User Management

• JWT-based authentication
• User registration and login
• Role-based access control (Admin and User roles)
• Password hashing with bcrypt
• User profile management

Face Recognition

• Face registration with multiple image captures
• Face recognition for attendance marking
• Uses face_recognition library (dlib-based)
• Stores face encodings locally using pickle format

Attendance Management

• Face recognition-based attendance marking
• Manual attendance management (Admin)
• Attendance history tracking
• Daily attendance status (Present/Absent)
• Time-in recording

Dashboards

• Admin Dashboard: User management, attendance overview, manual attendance updates
• Employee Dashboard: Personal attendance history and statistics
• Analytics Dashboard: Attendance trends, department performance, export functionality

Reporting

• Export attendance data to PDF, Excel, CSV, JSON formats
• Attendance statistics and analytics
• Department-wise analytics

Technology Stack

Backend

• FastAPI - Python web framework
• SQLite - Database with SQLAlchemy ORM
• face_recognition - Face recognition library (dlib-based)
• OpenCV - Image processing
• JWT - Authentication tokens
• Bcrypt - Password hashing

Frontend

• React 18 - UI framework
• Material-UI (MUI) - Component library
• React Router - Routing
• Recharts - Data visualization
• React Webcam - Camera access

Installation

Prerequisites

• Python 3.8 or higher
• Node.js 16 or higher
• Webcam for face recognition

Backend Setup

# Navigate to backend directory
cd backend

# Create virtual environment
python -m venv venv

# Activate virtual environment
# Windows:
venv\Scripts\activate
# macOS/Linux:
source venv/bin/activate

# Install dependencies
pip install -r requirements.txt

# Run the server
uvicorn main:app --reload --host 0.0.0.0 --port 8000

The backend API will be available at http://localhost:8000 API documentation available at http://localhost:8000/docs

Frontend Setup

# Navigate to frontend directory
cd frontend

# Install dependencies
npm install

# Start development server
npm start

The frontend will be available at http://localhost:3000

Usage

Initial Setup

1. Start both backend and frontend servers
2. Register a new user account
3. For the first user, run the migration script to assign admin role:

   cd backend
   python migrate_add_role.py

User Registration

1. Register with email and password
2. Login to your account
3. Navigate to Face Registration
4. Capture 5-6 face images for enrollment
5. Once registered, you can mark attendance using face recognition

Marking Attendance

1. Navigate to "Mark Attendance" page
2. Click "Mark Attendance" button
3. Position your face in front of the camera
4. System will recognize your face and mark attendance

Admin Functions

• View all users and their attendance records
• Manually mark attendance for users
• View analytics and export reports
• Update user information

Project Structure

Smart_Attendance_System/
├── backend/
│   ├── main.py                      # FastAPI application
│   ├── models.py                   # Database models
│   ├── schemas.py                  # Pydantic schemas
│   ├── database.py                 # Database configuration
│   ├── auth.py                     # Authentication utilities
│   ├── face_recognition_service.py # Face recognition logic
│   ├── migrate_add_role.py         # Role migration script
│   ├── requirements.txt            # Python dependencies
│   ├── dataset/                    # Face encoding storage (gitignored)
│   └── uploads/                    # Temporary uploads (gitignored)
│
├── frontend/
│   ├── public/
│   ├── src/
│   │   ├── components/             # React components
│   │   ├── services/               # API services
│   │   ├── App.js                  # Main app component
│   │   └── index.js                # Entry point
│   └── package.json
│
├── requirements.txt                # Root requirements (for scripts)
├── README.md
└── .gitignore

API Endpoints

Authentication

• POST /auth/register - User registration
• POST /auth/login - User login

Face Recognition

• POST /face/register - Register face data
• POST /attendance/mark - Mark attendance via face recognition

User

• GET /user/profile - Get user profile
• PUT /user/profile - Update user profile
• PUT /user/password - Change password
• GET /user/attendance - Get attendance history
• GET /user/attendance/stats - Get attendance statistics

Admin

• GET /admin/users - Get all users
• GET /admin/attendance - Get all attendance records
• PUT /admin/attendance/{id} - Update attendance record
• POST /admin/mark-absent - Mark users as absent
• POST /admin/attendance/bulk-update - Bulk update attendance

Analytics

• GET /analytics/dashboard - Get dashboard analytics
• GET /analytics/anomalies - Get anomaly detection data
• GET /analytics/report - Get report data

Full API documentation available at /docs when backend is running.

Configuration

Backend Environment Variables

Create a .env file in the backend directory (optional):

SECRET_KEY=your-secret-key-here
ACCESS_TOKEN_EXPIRE_MINUTES=30

Frontend Environment Variables

Create a .env file in the frontend directory (optional):

REACT_APP_API_URL=http://localhost:8000

Database

The system uses SQLite database which is automatically created on first run. Database file: backend/attendance_system.db

To reset the database, delete the .db file and restart the backend server.

Troubleshooting

Face Recognition Issues

• Ensure good lighting conditions
• Clear camera lens
• Register with 5-6 clear face images
• Face should be clearly visible in frame

Camera Access

• Allow camera permissions in browser
• Use HTTPS in production (required for camera access)
• Ensure no other application is using the camera

Installation Issues

• Ensure Python 3.8+ and Node.js 16+ are installed
• Use virtual environment for Python dependencies
• If face_recognition installation fails, install cmake and dlib dependencies first

License

This project is licensed under the MIT License.