The official Gradio implementation of Artist-Inator: Text-based, Gloss-aware Non-photorealistic Stylization.

J. Daniel Subias¹, Saul Daniel-Soriano¹, Diego Gutierrez¹ and Ana Serrano¹

¹Universidad de Zaragoza, I3A, Spain

In Eurographics Symposium on Rendering 2025 (Oral Presentation)

# Clone repository and enter in the folder
git clone [email protected]:dsubias/Artist-Inator.git
cd Artist-Inator

# Download pretrained model
bash download_model.sh

# Create a python environment
python -m venv artist-inator_env
source artist-inator_env/bin/activate
pip install -r requirements.txt

# Run the gradio app
python gradio_app.py

# Deactivate the python environment
deactivate

If everything works without errors, you should see an interface like this:

Python 3 dependencies:

• PyTorch 2.7.1
• CUDA 12.4
• Gradio 5.33.0
• Diffusers

Download the pre-trained ControlNet model:

bash download_model.sh

We provide a requirements file including all of the above dependencies to create an environment. Create the python environment artist-inator_env by running:

python -m venv artist-inator_env
source artist-inator_env/bin/activate
pip install -r requirements.txt

@article{10.1111:cgf.70182,
journal = {Computer Graphics Forum},
title = {{Artist-Inator: Text-based, Gloss-aware Non-photorealistic Stylization}},
author = {Subias, Jose Daniel and Daniel-Soriano, Saúl and Gutierrez, Diego and Serrano, Ana},
year = {2025},
publisher = {The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {10.1111/cgf.70182}
}

This code refers to the following two projects:

[1] StyLit, Ebsynth

[2] ControlNet, Diffusers

This work was supported by the project PID2022-141539NB-I00, funded by MICIU/AEI/10.13039/501100011033 and by ERDF, EU; by the Government of Aragon’s Departamento de Ciencia, Universidad y Sociedad del Conocimiento through the Reference Research Group “Graphics and Imaging Lab” (ref. T34_23R); and by the Government of Aragon’s Departamento de Educación, Ciencia y Universidades through the project “HUMAN-VR: Development of a Computational Model for Virtual Reality Perception” (PROY_T25_24). J. Daniel Subias was supported by the CUS/702/2022 predoctoral grant.

[email protected] (Daniel Subías)

The code from this repository is from a research project, under active development. Please use it with caution and contact us if you encounter any issue.

This software is under GNU General Public License Version 3 (GPLv3), please see GNU License For commercial purposes, please contact the authors.