https://github.com/lucasalegre/selfieart

SelfieArt: Interactive Multi-Style Transfer for Selfies and Videos with Soft Transitions
https://github.com/lucasalegre/selfieart

face-parsing multi-style-transfer style-transfer

Last synced: 2 months ago
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SelfieArt: Interactive Multi-Style Transfer for Selfies and Videos with Soft Transitions

• Host: GitHub
• URL: https://github.com/lucasalegre/selfieart
• Owner: LucasAlegre
• License: mit
• Created: 2020-10-15T13:39:15.000Z (over 4 years ago)
• Default Branch: main
• Last Pushed: 2022-12-29T16:06:43.000Z (over 2 years ago)
• Last Synced: 2025-04-14T17:05:56.576Z (2 months ago)
• Topics: face-parsing, multi-style-transfer, style-transfer
• Language: Python
• Homepage:
• Size: 60.9 MB
• Stars: 8
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE
  • Citation: CITATION.bib

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README

        
# SelfieArt

SelfieArt: Interactive Multi-Style Transfer for Selfies and Videos with Soft Transitions

![](images/selfieart.gif)

## Install

We recommend the use of our conda environment:

```

conda env create -f environment.yml

```

## Run

To run SelfieArt GUI application:

```

python run.py

```

## Acknowledgements

Code for SelfieArt is built on top of:

- [face-parsing.PyTorch](https://github.com/zllrunning/face-parsing.PyTorch)

- [PyTorch-Multi-Style-Transfer](https://github.com/zhanghang1989/PyTorch-Multi-Style-Transfer)

- [Neural Transfer Using PyTorch](https://pytorch.org/tutorials/advanced/neural_style_tutorial.html)

## Citation

```

@InProceedings{AlegreOliveira2020,

  author    = {Alegre, Lucas N. and Oliveira, Manuel M.},

  title     = {SelfieArt: Interactive Multi-Style Transfer for Selfies and Videos with Soft Transitions},

  booktitle = {Proceedings of the 2020 33rd SIBGRAPI Conference on Graphics, Patterns and Images},

  year      = {2020}

}

```