This project is a Face Recognition System that generates face encodings for stored data and uses these encodings to recognize new faces. When a new face is recognized, the data is added to a real-time database using Firebase.
- 🔢 Face Encoding Generation: Generates unique encodings for faces stored in the database.
- 🕵️ Real-Time Face Recognition: Recognizes new faces using the generated encodings.
- 🔄 Real-Time Database Integration: Adds recognized face data to Firebase in real-time.
- Python
- OpenCV
- dlib
- Firebase
To get started with the project, follow these steps:
-
Clone the Repository:
git clone https://github.com/yourusername/face-recognition-system.git cd face-recognition-system
-
Create and Activate Virtual Environment:
python -m venv env source env/bin/activate # On Windows, use `env\Scripts\activate`
-
Install Dependencies:
pip install -r requirements.txt
-
Setup Firebase:
- Create a Firebase project in the Firebase Console.
- Add a real-time database to your project.
- Download the
serviceAccountKey.json
file from Firebase and place it in your project directory.
-
Generate Face Encodings:
- Run the script to generate face encodings for stored data.
python EncodingGenerator.py
-
Recognize New Faces:
- Run the script to start recognizing new faces and adding data to Firebase in real-time.
python main.py
Make sure to configure your Firebase settings in the firebase_config.json
file. Here is a template:
{
"apiKey": "YOUR_API_KEY",
"authDomain": "YOUR_PROJECT_ID.firebaseapp.com",
"databaseURL": "https://YOUR_PROJECT_ID.firebaseio.com",
"storageBucket": "YOUR_PROJECT_ID.appspot.com",
"serviceAccount": "serviceAccountKey.json"
}
Contributions are welcome! Please fork the repository and submit a pull request with your changes.
This project is licensed under the MIT License - see the LICENSE file for details.
If you have any questions or feedback, feel free to reach out to me at miteshgupta2711@gmail.com.