Lunar.Face

A desktop application with facial recognition embedded. It's built with PyQt5 and using Azure Cognitive Service Face API.

Python Version

Some of the libraries used in this project, such as azure-cognitiveservices-vision-face, are only working up to Python 3.8. Hence, it is recommended to develop this project using only Python 3.8.

Local Development and Use

1. Checkout the codes to a working directory;
2. Create a virtual environment in the working directory, execute the following command:
   python3 -m venv venv
3. Activate the virtual environment on Windows, run:
   call venv/scripts/activate.bat
   On Mac and Linux, use:
   source venv/bin/activate
4. Install the required packages with the command pip install -r requirements.txt;
5. Create Cognitive Service on the Azure Portal and set its API key and endpoint in the environment variables;

    SET AZURE_COGNITIVE_SERVICE_KEY=...
    SET AZURE_COGNITIVE_SERVICE_ENDPOINT=...
   

   Note: The reason of setting the key and endpoint in the environment variables is to auto fill them into the app. You can choose not to set them in the environment but instead, manually key them to the app for every launch of the app;
6. Run the program with the command python main.py;
7. Browse an image with real human face;
8. Enjoy the result.

Demo

Important Packages

• PyQt5;
• matplotlib;
• Microsoft Azure Cognitive Services Face Client Library;
• PyQtChart;
• Qt-Material.

License

This library is distributed under the GPL-3.0 License found in the LICENSE file.