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.

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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.

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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"

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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.

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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.

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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.

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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.

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Screenshots

Add relevant screenshots showcasing:

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

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Contributing

Contributions are welcome! Please:

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

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License

This project is licensed under the MIT License.

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Acknowledgments

• OpenCV
• Face Recognition Library
• Firebase

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Contact

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

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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.