Face Recognition Attendance System

A modern, web-based attendance management system that uses facial recognition technology to automatically mark attendance. Built with Flask, OpenCV, and face_recognition library.

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🚀 Features

🔍 Core Functionality

• Real-time Face Recognition: Instant face detection and recognition using webcam
• Automatic Attendance Marking: Automatically records attendance when recognized faces are detected
• Web-based Interface: Modern, responsive web interface for easy management
• Database Storage: SQLite database for reliable attendance data storage
• Training Image Management: Upload and manage training images for face recognition

📊 Dashboard & Analytics

• Real-time Dashboard: View current attendance statistics and recent records
• Attendance Reports: Generate detailed reports with date range filtering
• Statistics Overview: Total records, today's attendance, and unique people count
• Historical Data: Access complete attendance history

👥 User Management

• Training Image Upload: Add new people to the system with photo uploads
• Name Management: Associate names with training images
• Training Image Deletion: Remove people from the recognition system

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🧰 Technology Stack

• Backend: Flask (Python web framework)
• Face Recognition: face_recognition library (dlib-based)
• Computer Vision: OpenCV
• Database: SQLite
• Frontend: HTML5, CSS3, JavaScript
• Image Processing: PIL (Python Imaging Library)
• Data Analysis: Pandas

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🛠 Prerequisites

• Python 3.7 or higher
• Webcam for face capture
• Windows 10/11 (tested on Windows 10.0.26100)

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⚙️ Installation

1. Clone the repository

git clone <https://github.com/rbpata/Face-Recognition-Attendance-System.git>
cd Attendance-System

2. Install Python dependencies

pip install -r requirements.txt

3. Install dlib (if needed)

pip install dlib-19.24.1-cp311-cp311-win_amd64.whl

4. Initialize the database

• The database will be automatically created when you run the application

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🖥 Usage

🌐 Web Application Mode (Recommended)

1. Start the Flask application

python app.py

2. Access the web interface

• Go to http://localhost:5000

3. Navigate through the interface:

• Home: Overview and quick access
• Dashboard: Attendance statistics
• Capture: Real-time recognition
• Upload: Add people with images
• Reports: View/export attendance logs

🧪 Command Line Mode

python main.py

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🗂 Project Structure

Attendance-System/
├── app.py                 # Flask web app
├── main.py               # CLI attendance mode
├── requirements.txt      # Python packages
├── templates/            # HTML templates
├── static/               # CSS/JS assets
├── Training_images/      # Known faces
├── Unknown/              # Unknown captures
├── attendance.db         # SQLite DB
└── Attendance.csv        # Legacy CSV log

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🔬 How It Works

🧠 Face Recognition Flow

1. Upload face images to Training_images
2. Encodes facial features
3. Captures live webcam feed
4. Matches detected faces with training data
5. Logs attendance automatically

🌐 Web Flow

• Upload → Capture → Dashboard → Reports

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🧾 Database Schema

CREATE TABLE attendance (
    id INTEGER PRIMARY KEY AUTOINCREMENT,
    name TEXT NOT NULL,
    timestamp DATETIME DEFAULT CURRENT_TIMESTAMP,
    date DATE DEFAULT CURRENT_DATE
);

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🎨 User Interface & Screenshots

💻 UI Overview

• Responsive design with intuitive flow
• Real-time attendance overlay
• Bootstrap styling for consistency

📷 Screenshots

🔹 Input Form

🔹 Attendance Output

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🛠 Troubleshooting

Common Issues & Fixes

1. Camera not working

   • Check if another app is using it
   • Verify browser permissions

2. No face detected

   • Ensure clear, front-facing images
   • Check lighting conditions

3. Installation errors

   • Use Python 3.7+
   • Use provided dlib wheel for Windows

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📃 License

MIT License. Feel free to use and modify.