--- tags: - Keras - gan - tensorflow - conditional-image-generation --- ## rasm Arabic art using GANs. We currently have two models for generating calligraphy and mosaics. ## Notebooks
Name Notebook
Visualization
## Visualization A set of functions for vis, interpolation and animation. Mostly tested in colab notebooks. ### Load Model ```python from rasm import Rasm model = Rasm(mode = 'calligraphy') model = Rasm(mode = 'mosaics') ``` ### Generate random ```python model.generate_randomly() ``` ### Generate grid ```python model.generate_grid() ``` ### Generate animation ```python model.generate_animation(size = 2, steps = 20) ``` ![alt text](video.gif) ## Sample Models ### Mosaics ![alt text](imgs/mosaic.png) ![alt text](imgs/mosaicsv2.png) ![alt text](imgs/mosaicsv3.png) ![alt text](imgs/mosaicsv4.png) ### Calligraphy ![alt text](imgs/calligraphyv2.PNG) ![alt text](imgs/calligraphyv3.png) ![alt text](imgs/calligraphyv4.png) ![alt text](imgs/calligraphyv5.png) ## References - Gan-surgery: https://github.com/aydao/stylegan2-surgery - WikiArt model: https://github.com/pbaylies/stylegan2 - Starter-Notebook: https://github.com/Hephyrius/Stylegan2-Ada-Google-Colab-Starter-Notebook/