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# diffvg
Differentiable Rasterizer for Vector Graphics
https://people.csail.mit.edu/tzumao/diffvg
diffvg is a differentiable rasterizer for 2D vector graphics. See the webpage for more info.
# Install
```
git submodule update --init --recursive
conda install -y pytorch torchvision -c pytorch
conda install -y numpy
conda install -y scikit-image
conda install -y -c anaconda cmake
conda install -y -c conda-forge ffmpeg
pip install svgwrite
pip install svgpathtools
pip install cssutils
pip install numba
pip install torch-tools
pip install visdom
python setup.py install
```
# Install using poetry
## prerequisite
install python 3.7, poetry and ffmpeg
```
# install poetry (mac, linux)
curl -sSL https://raw.githubusercontent.com/python-poetry/poetry/master/get-poetry.py | python -
# install ffmpeg
(macos)
brew install ffmpeg
(linux)
sudo apt install ffmpeg
or use conda
conda install -y -c conda-forge ffmpeg
```
## Install python packages
```
# install all python dependencies
poetry install
# install pydiffvg
poetry run python setup.py install
```
Now to run the apps, just add `poetry run` before each of the commands below, e.g.
```
poetry run python single_circle.py
```
# Building in debug mode
```
python setup.py build --debug install
```
# Run
```
cd apps
```
Optimizing a single circle to a target.
```
python single_circle.py
```
Finite difference comparison.
```
finite_difference_comp.py [-h] [--size_scale SIZE_SCALE]
[--clamping_factor CLAMPING_FACTOR]
[--use_prefiltering USE_PREFILTERING]
svg_file
```
e.g.,
```
python finite_difference_comp.py imgs/tiger.svg
```
Interactive editor
```
python svg_brush.py
```
Painterly rendering
```
painterly_rendering.py [-h] [--num_paths NUM_PATHS]
[--max_width MAX_WIDTH] [--use_lpips_loss]
[--num_iter NUM_ITER] [--use_blob]
target
```
e.g.,
```
python painterly_rendering.py imgs/fallingwater.jpg --num_paths 2048 --max_width 4.0 --use_lpips_loss
```
Image vectorization
```
python refine_svg.py [-h] [--use_lpips_loss] [--num_iter NUM_ITER] svg target
```
e.g.,
```
python refine_svg.py imgs/flower.svg imgs/flower.jpg
```
Seam carving
```
python seam_carving.py [-h] [--svg SVG] [--optim_steps OPTIM_STEPS]
```
e.g.,
```
python seam_carving.py imgs/hokusai.svg
```
Vector variational autoencoder & vector GAN:
For the GAN models, see `apps/generative_models/train_gan.py`. Generate samples from a pretrained using `apps/generative_models/eval_gan.py`.
For the VAE models, see `apps/generative_models/mnist_vae.py`.
If you use diffvg in your academic work, please cite
```
@article{Li:2020:DVG,
title = {Differentiable Vector Graphics Rasterization for Editing and Learning},
author = {Li, Tzu-Mao and Luk\'{a}\v{c}, Michal and Gharbi Micha\"{e}l and Jonathan Ragan-Kelley},
journal = {ACM Trans. Graph. (Proc. SIGGRAPH Asia)},
volume = {39},
number = {6},
pages = {193:1--193:15},
year = {2020}
}
```
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