Blagoj Mitrevski† • Arina Rak† • Julian Schnitzler† • Chengkun Li† • Andrii Maksai‡ • Jesse Berent • Claudiu Musat
† Joint first authors | ‡ Corresponding author
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October 2024: We release Small-p on Hugging Face!
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October 2024: Our work is now featured on the Google Research Blog!
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February 2024: The InkSight Demo on Hugging Face is live!
To set up and run the Gradio Playground locally, you can use the following steps:
# Clone the huggingface space
git clone https://huggingface.co/spaces/Derendering/Model-Output-Playground
# Install the dependencies
cd Model-Output-Playground
pip install -r requirements.txt
Then you can run the following command to interact with the playground:
# Run the Gradio Playground
python app.py
We provide open resources for InkSight public version model. Choose the options that best fit your needs:
- Public version model for CPU/GPU inference (494 MB)
- Hugging Face model for CPU/GPU inference: InkSight Small-p.
- Public version model for TPU inference (494 MB)
- Supplementary material for the paper. This is used in the example colab linked below, which automatically downloads this content.
- Example code in the form of a Colab notebook that showcases model inference results on several samples and example code to run the inference.
- Samples of model outputs of huggingface demo.
The code in this repository is released under the Apache 2 license.
Please note: This is not an officially supported Google product.
If you find our work useful for your research and applications, please cite using this BibTeX:
@article{mitrevski2024inksight,
title={InkSight: Offline-to-Online Handwriting Conversion by Learning to Read and Write},
author={Mitrevski, Blagoj and Rak, Arina and Schnitzler, Julian and Li, Chengkun and Maksai, Andrii and Berent, Jesse and Musat, Claudiu},
journal={arXiv preprint arXiv:2402.05804},
year={2024}
}