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<h3 align="center">Modelling complex vector drawings with stroke-clouds</h3> <p align="center"> ICLR 2024 Poster Paper <br /> <br /> <br /> <a href="https://iclr.cc/virtual/2024/poster/18757">Paper</a> · <a href="https://drive.google.com/file/d/1rv8MGfiAv6lwddGiSLTCqK2Mfltqnatk/view?usp=sharing">Data</a> · <a href="https://drive.google.com/drive/folders/1e61EzE33T7foYsLqr-B3IGHLtgVX2MPD?usp=sharing">Models</a> </p> </div> <!-- ABOUT THE PROJECT --><img src="https://github.com/Co-do/Stroke-Cloud/assets/123647750/411131f4-4826-4763-a485-69cd929a8e26" width="200" height="200"> <img src="https://github.com/Co-do/Stroke-Cloud/assets/123647750/ea4ce9be-d05c-4393-9ed8-91152aff3c12" width="200" height="200"> <img src="https://github.com/Co-do/Stroke-Cloud/assets/123647750/4f554f6f-0f9b-464e-9bc8-6faffe1392e0" width="200" height="200"> <img src="https://github.com/Co-do/Stroke-Cloud/assets/123647750/4172389c-a0b4-4ecd-866f-296790c0706e" width="200" height="200">
<!-- GETTING STARTED -->Introduction
This is the offical repository for "Modelling complex vector drawings with stroke-clouds". The data set and pre-trained models can be downloaded from the links given. Instructions for inference and training both the srm and lsg are given.
Environment
lxml - 4.9
lightning - 2.0.9
pytorch-lightning - 2.0.3
torch - 2.2.0
Training
SRM:
- Add your wandb key or change the logger in srm_train.py.
- Download the training data.
- Run srm_train.py
LSG:
- Generate latent codes with srm_test.py
- Add your wandb key or change the logger in lsg_train.py.
- Run lsg_train.py
Inference
- Download the models and run lsg_test.py
- Or run lsg_test.py with your own trained models.
License
Distributed under the MIT License. See LICENSE.txt
for more information.
Contact
Alexander Ashcroft - aa05377@surrey.ac.uk