# SOAT

**Repository Path**: as85207/SOAT

## Basic Information

- **Project Name**: SOAT
- **Description**: Official PyTorch repo for StyleGAN of All Trades: Image Manipulation with Only Pretrained StyleGAN.
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2021-11-29
- **Last Updated**: 2021-11-29

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# StyleGAN of All Trades: Image Manipulation with Only Pretrained StyleGAN
![](teaser.jpg)

This is the PyTorch implementation of [StyleGAN of All Trades: Image Manipulation with Only Pretrained StyleGAN](https://arxiv.org/abs/2111.01619). [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/mchong6/SOAT/blob/main/infinity.ipynb)


>**Abstract:**<br>
Recently, StyleGAN has enabled various image manipulation and editing tasks thanks to the high-quality generation and the disentangled latent space. However, additional architectures or task-specific training paradigms are usually required for different tasks. In this work, we take a deeper look at the spatial properties of StyleGAN. We show that with a pretrained StyleGAN along with some operations, without any additional architecture, we can perform comparably to the state-of-the-art methods on various tasks, including image blending, panorama generation, generation from a single image, controllable and local multimodal image to image translation, and attributes transfer.


## How to use
Everything to get started is in the [colab notebook](https://colab.research.google.com/github/mchong6/SOAT/blob/main/infinity.ipynb).

## Toonification
For toonification, you can train a new model yourself by running
```bash
python train.py
```
For disney toonification, we use the disney dataset [here](https://github.com/justinpinkney/toonify). Feel free to experiment with different datasets.

## Citation
If you use this code or ideas from our paper, please cite our paper:
```
@article{chong2021stylegan,
  title={StyleGAN of All Trades: Image Manipulation with Only Pretrained StyleGAN},
  author={Chong, Min Jin and Lee, Hsin-Ying and Forsyth, David},
  journal={arXiv preprint arXiv:2111.01619},
  year={2021}
}
```

## Acknowledgments
This code borrows from [StyleGAN2 by rosalinity](https://github.com/rosinality/stylegan2-pytorch)