🌟 Project Overview

The OpenCV-FaceRecognition-Database project is an automated attendance system designed for workplaces and schools. The system utilizes Orange Pi 5 Plus, a Logitech HD C720 Camera, and is powered by OpenCV and Firebase. By implementing real-time face detection and recognition, the project replaces traditional attendance methods with a seamless, secure, and contactless experience.

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🛠️ Technologies Used

• Programming Language: Python

• Libraries: OpenCV, Firebase Admin SDK, face_recognition, NumPy

• Hardware:

  • Orange Pi 5 Plus
  • Logitech HD C720 Camera
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• Database: Firebase Realtime Database, Firebase Storage

• Development Environment: PyCharm IDE

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✨ Key Features

• Real-time face detection and recognition.
• Automated attendance tracking and logging in Firebase.
• Secure image storage and data management via Firebase.
• User-friendly interface displaying employee/student information.

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📥 Installation and Usage

1. Environment Setup

Clone the repository:

git clone https://github.com/EricTra/OpenCV-FaceRecognition-Database.git
cd OpenCV-FaceRecognition-Database

Install required dependencies:

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

2. Firebase Configuration

• Create a Firebase project on Firebase Console.
• Download the serviceAccountKey.json file and place it in the root directory of the project.
• Update the database URL and storage bucket in the source code (Main.py, AddDataToDatabase.py, etc.) to match your Firebase configuration.

3. Running the Application

1. Encode facial data and save it to a file:

python EncodeGenerator.py

2. Add user data to Firebase:

python AddDataToDatabase.py

3. Start the facial recognition system:

python Main.py

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📸 Demo and Screenshots

1. User interface during facial recognition:

2. Real-time data stored in Firebase:

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📧 Contact Information

• Author: Trà Quang Duy
• Email: [email protected]
• LinkedIn: https://www.linkedin.com/in/traquangduy/