Skip to content

A python module with scripts and jupyter/colab notebooks for creating 2d vector graphics using machine learning.

Notifications You must be signed in to change notification settings

duskvirkus/compose

Repository files navigation

Compose

⚠️ This project is still in development. Please report bug but don't expect everything to work very smoothly.

A python module to streamline working with 2D and 3D vector graphics in machine learning projects.

Much of the philosophy of this module is based on Processing and p5.js. In other words it favors more accessible syntax over complete efficiency.

Notebooks

Single Image Notebook: ./notebooks/compose_test_01_py.ipynb

Open In Colab

Video Notebook (very hacky): ./notebooks/compose_test_04_py.ipynb

Open In Colab

Installing Locally

Platform

Recommended python version is 3.7. Ubuntu based Linux is currently the only supported platform. If you run into issues on other platforms feel free to file an issue but it will be low priority.

Anaconda Setup

conda create -n compose python=3.7
conda activate compose
conda install -c conda-forge jupyterlab
conda install -c anaconda ipykernel
python -m ipykernel install --user --name=compose

Dependancies

sudo ./scripts/install/platform/ubuntu.sh
sudo apt upgrade
git submodule update --init --recursive
python scripts/install/pytorch.py # to make sure you get the correct nvidia compile
pip install -r requirements.txt
cd diffvg
python setup.py install
cd ..
python setup.py install

Documentation

Currently documentation could use some work and can only be built locally. See CONTRIBUTING.md for some instructions.

Thanks

This project would not be possible without the work of the creators of diffvg Tzu-Mao Li, Michal Lukáč, Michaël Gharbi, and Jonathan Ragan-Kelley.

Thanks to Peter Schaldenbrand, Zhixuan Liu, Jean Oh (creators of StyleCLIPDraw) for example of getting diffvg working on colab.

About

A python module with scripts and jupyter/colab notebooks for creating 2d vector graphics using machine learning.

Topics

Resources

Stars

Watchers

Forks

Packages

No packages published