/kg_ml_app

Use machine learning models for hadron classification on KASCADE data

Primary LanguagePython

README

About

Streamlit Web App to perform gamma hadron classification based on data by KASCADE experiment.

image

Dataset is taken from KASCADE Cosmic Ray Data Centre. The application is developed for educational purposes.

How to:

Docker

  • Biuld the image: docker build --tag app:1.1 .
  • Run the app in the container: docker run --publish 8344:8344 -it app:1.1

Ready!

Virtual environment

If you don't want to run the app in the container, you can virtual environment using

pipenv shell

and when run the app manually using

streamlit run kg_ml_app.py --server.port 8344

(or any other port you prefer).

Warning: streamlit doesn't free the port itself! Use kill -9 $(lsof -t -i:8344) for this purpose.

Acknowledgements

KASCADE Cosmic Ray Data Centre, for providing the data for the machine learning pipeline.

Streamlit, for the open-source library for rapid prototyping.

Astroparticle Physics Research group, for fruitful discussions and inspiration.