This is a face recognition application built with Python using OpenCV and Tkinter. It allows users to log in and register new users by capturing their facial images through a webcam.
- Login: Users can log in by recognizing their face from the webcam feed.
- Register New User: New users can register by capturing their face and providing a username.
- Real-time Webcam Feed: Displays the webcam feed in real-time.
Watch a demonstration of the virtual painter application on YouTube: Face Recognition Application Demo
- click==8.1.7
- cmake==3.17.2
- colorama==0.4.6
- dlib==19.18.0
- face-recognition==1.3.0
- face_recognition_models==0.3.0
- numpy==1.26.4
- opencv-python==4.9.0.80
- Pillow==9.2.0
- Face Recognition CLI tool (to perform face recognition, install from face_recognition GitHub)
- Clone the repository:
git clone https://github.com/TOUZOUZ-Adnane/Face-Recognition.git
- Navigate into the project directory:
cd Face-Recognition - Create a virtual environment:
python -m venv venv
- Activate the virtual environment:
- On Windows:
venv\Scripts\activate
- On macOS/Linux:
source venv/bin/activate
- Install the required Python libraries:
pip install -r requirements.txt
- Run the application:
python main.py
main.py: Main application script.util.py: Utility functions for creating UI elements and displaying messages.assets/known/: Directory to store registered user images.assets/unknown.jpg: Temporary file to store the captured image for login attempts.
- App Class: The main class handling the application logic including webcam feed, login, and user registration.
- Utility Functions: Defined in
util.pyto create buttons, labels, and message boxes.
- Ensure that your webcam is properly connected and accessible.
- Verify that all dependencies are correctly installed.
- If the Face Recognition CLI tool is not working, refer to its documentation for installation and usage.
For any issues or questions, please contact me via:
- Email: [email protected]
- LinkedIn: Adnane Touzouz