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