otroivan/Whitebox-Style-Transfer-Editing
White-box Style Transfer Editing (WISE) Demo
This app demonstrates the editing capabilities of the White-box Style Transfer Editing (WISE) framework. It optimizes the parameters of classical image processing filters to match a given style image. After optimization, parameters can be tuned by hand to achieve a desired look.
How does it work?
We provide a small stylization effect that contains several filters such as bump mapping or edge enhancement that can be optimized. The optimization yields so-called parameter masks, which contain per-pixel parameter settings for each filter.
🚀 Try it out 🚀
Our demo is now on huggingface: [huggingface/Whitebox-Style-Transfer-Editing](https://huggingface.co/spaces/MaxReimann/Whitebox-Style-Transfer-Editing)
To run locally, clone the repo recursively and install the dependencies in requirements.txt. Set HUGGINGFACE to false in democonfig.py. Then run the streamlit app using `streamlit run Whiteboxstyle_transfer.py`
Links & Paper
Project page, arxiv link, framework code
"WISE: Whitebox Image Stylization by Example-based Learning", by Winfried Lötzsch, Max Reimann, Martin Büßemeyer, Amir Semmo, Jürgen Döllner, Matthias Trapp, in ECCV 2022
Further notes
Pull Requests and further improvements welcome. Please note that the shown effect is a minimal pipeline in terms of stylization capability, the much more feature-rich oilpaint and watercolor pipelines we show in our ECCV paper cannot be open-sourced due to IP reasons.