AI-Powered Face Recognition System with Real-time Database

Table of Contents

• Introduction
• Features
• Requirements
• Installation
• Usage
• Configuration
• Contributing

Introduction

Welcome to the AI-Powered Face Recognition System with Real-time Database repository. This project allows you to create an attendance marking system using computer vision and a real-time database. Users can mark their attendance by simply showing their faces to the webcam, and the system will recognize and log their attendance in a database.

Features

• Real-time face recognition
• Attendance logging with timestamps
• Firebase real-time database integration
• Easy-to-use user interface

Requirements

Before getting started, ensure you have the following requirements:

• Python 3.7
• OpenCV (cv2)
• cvzone
• face_recognition
• Firebase Admin SDK

Installation

1. Clone this repository to your local machine:

   git clone https://github.com/PinsaraPerera/AI_powered_faceRecognition_system_with_realtime_database.git

2. Install the required Python packages:

   pip install opencv-python cvzone face-recognition firebase-admin

Usage

1. Create a Firebase project and obtain the Firebase Admin SDK JSON key file.

2. Replace serviceAccountKey.json in the project folder with your Firebase Admin SDK JSON key.

3. Prepare 216px * 216px images of students and store them in the Images folder.

4. Run the application:

   python EncodeGenerator.py

5. Run the application:

   python main.py

6. Use the application to mark attendance by showing your face to the webcam.

Configuration

You can customize the project by modifying the following parameters in the code:

• Firebase Real-time Database URL: Replace with your Firebase Database URL.
• Storage Bucket: Replace with your Firebase Storage bucket.

Contributing

Contributions are welcome! Feel free to submit issues and pull requests to help improve this project.