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Face Recognition System

This GitHub repository contains a Face Recognition System built using Python, OpenCV, and Firebase. The system can recognize faces, manage attendance records, and store user data in a Firebase Realtime Database. It includes two main Python scripts: Face_Recognition.py and EncodeGenerator.py.

Features

  • Real-Time Face Recognition: Detects and recognizes faces using the face_recognition library.
  • Attendance Management: Logs attendance with timestamps and updates total attendance count.
  • Firebase Integration: Uses Firebase Realtime Database and Cloud Storage for data storage and retrieval.
  • Encoding Generation: Generates face encodings from images and stores them in a pickle file for quick access.

Prerequisites

1. Python Dependencies

Install the following packages:

pip install opencv-python face_recognition numpy cvzone firebase-admin python-dotenv

2. Firebase Setup

  • Realtime Database: Enable and configure Firebase Realtime Database.
  • Cloud Storage: Configure Firebase Cloud Storage.
  • Credentials: Download the Firebase credentials JSON file and place it in the project directory.

3. Environment Variables

Create a .env file and add:

FIREBASE_DATABASE_URL = "your-firebase-database-url"
FIREBASE_STORAGE_BUCKET = "your-firebase-storage-bucket"
FIREBASE_CREDENTIALS = "path-to-your-firebase-credentials.json"

Installation

  1. Clone the repository: 
    git clone https://github.com/HariPasapuleti/Face-Recognition.git
cd Face-Recognition
  2. Install dependencies: 
    pip install -r requirements.txt
  3. Set up resources:
    • Create a resource folder and add:
      • A background image (background.png).
      • A modes folder containing mode images.
    • Create an images folder for student images.

Usage

Step 1: Generate Encodings

Run the EncodeGenerator.py script to generate face encodings from student images:

python EncodeGenerator.py

This script:

  • Uploads student images to Firebase Storage.
  • Generates a EncodFile.p file containing face encodings and IDs.

Step 2: Run Face Recognition

Run the face_recognition.py script to start the recognition system:

python Face_Recognition.py

Press n to exit the program.

File Structure

Main Files

  • EncodeGenerator.py:
    • Generates face encodings and uploads images to Firebase.
  • Face_Recognition.py:
    • Detects faces in real time, recognizes them, and logs attendance.

Resources

  • resource/:
    • background.png: Background image for UI.
    • modes/: Images representing different modes in the UI.
  • images/:
    • Stores student images for encoding.

Firebase Configuration

Realtime Database Structure

{
  "Students": {
    "123": {
      "name": "Hari Pasapuleti",
      "gender": "Male",
      "company": "XYZ Corp",
      "id": "123",
      "nationality": "India",
      "Joined year": "2023",
      "total attendance": 5,
      "last attendance time": "2025-02-01 10:00:00"
    }
  }
}

Cloud Storage

Store student images in the images/ folder within Firebase Storage.

Screenshots

Add relevant screenshots showcasing:

  • Application UI.
  • Firebase setup.
  • Sample outputs.

Contributing

Contributions are welcome! Please:

  1. Open an issue for bugs or feature requests.
  2. Submit a pull request for fixes or enhancements.

License

This project is licensed under the MIT License.

Acknowledgments

Contact

For any queries, feel free to reach out via Email.

Optimizations:

  1. Improved section organization with clear headings.
  2. Simplified repetitive instructions into concise steps.
  3. Clarified resource and setup details for better user experience.
  4. Added proper Markdown formatting for readability.