# draggan

**Repository Path**: jiyilee-open/draggan

## Basic Information

- **Project Name**: draggan
- **Description**: DragGAN 是由 Google 的研究人员与 Max Planck 信息学研究所和麻省理工学院 CSAIL 一起开发的项目，是一个非常直观的图像编辑工具，用户只需要控制图像中的
- **Primary Language**: Python
- **License**: Not specified
- **Default Branch**: main
- **Homepage**: https://www.oschina.net/p/draggan
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 10
- **Created**: 2023-06-26
- **Last Updated**: 2023-06-26

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

<p align="center">

  <h1 align="center">Drag Your GAN: Interactive Point-based Manipulation on the Generative Image Manifold</h1>
  <p align="center">
    <a href="https://xingangpan.github.io/"><strong>Xingang Pan</strong></a>
    ·
    <a href="https://ayushtewari.com/"><strong>Ayush Tewari</strong></a>
    ·
    <a href="https://people.mpi-inf.mpg.de/~tleimkue/"><strong>Thomas Leimkühler</strong></a>
    ·
    <a href="https://lingjie0206.github.io/"><strong>Lingjie Liu</strong></a>
    ·
    <a href="https://www.meka.page/"><strong>Abhimitra Meka</strong></a>
    ·
    <a href="http://www.mpi-inf.mpg.de/~theobalt/"><strong>Christian Theobalt</strong></a>
  </p>
  <h2 align="center">SIGGRAPH 2023 Conference Proceedings</h2>
  <div align="center">
    <img src="DragGAN.gif", width="600">
  </div>

  <p align="center">
  <br>
    <a href="https://pytorch.org/get-started/locally/"><img alt="PyTorch" src="https://img.shields.io/badge/PyTorch-ee4c2c?logo=pytorch&logoColor=white"></a>
    <a href="https://twitter.com/XingangP"><img alt='Twitter' src="https://img.shields.io/twitter/follow/XingangP?label=%40XingangP"></a>
    <a href="https://arxiv.org/abs/2305.10973">
      <img src='https://img.shields.io/badge/Paper-PDF-green?style=for-the-badge&logo=adobeacrobatreader&logoWidth=20&logoColor=white&labelColor=66cc00&color=94DD15' alt='Paper PDF'>
    </a>
    <a href='https://vcai.mpi-inf.mpg.de/projects/DragGAN/'>
      <img src='https://img.shields.io/badge/DragGAN-Page-orange?style=for-the-badge&logo=Google%20chrome&logoColor=white&labelColor=D35400' alt='Project Page'></a>
    <a href="https://huggingface.co/spaces/radames/DragGan"><img alt="Huggingface" src="https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-DragGAN-orange"></a>
  </p>
</p>

## Requirements

Please follow the requirements of [https://github.com/NVlabs/stylegan3](https://github.com/NVlabs/stylegan3).

## Download pre-trained StyleGAN2 weights

To download pre-trained weights, simply run:
```sh
sh scripts/download_model.sh
```
If you want to try StyleGAN-Human and the Landscapes HQ (LHQ) dataset, please download weights from these links: [StyleGAN-Human](https://drive.google.com/file/d/1dlFEHbu-WzQWJl7nBBZYcTyo000H9hVm/view?usp=sharing), [LHQ](https://drive.google.com/file/d/16twEf0T9QINAEoMsWefoWiyhcTd-aiWc/view?usp=sharing), and put them under `./checkpoints`.

Feel free to try other pretrained StyleGAN.

## Run DragGAN GUI

To start the DragGAN GUI, simply run:
```sh
sh scripts/gui.sh
```

This GUI supports editing GAN-generated images. To edit a real image, you need to first perform GAN inversion using tools like [PTI](https://github.com/danielroich/PTI). Then load the new latent code and model weights to the GUI.

You can run DragGAN Gradio demo as well:
```sh
python visualizer_drag_gradio.py
```

## Acknowledgement

This code is developed based on [StyleGAN3](https://github.com/NVlabs/stylegan3). Part of the code is borrowed from [StyleGAN-Human](https://github.com/stylegan-human/StyleGAN-Human).

## License

The code related to the DragGAN algorithm is licensed under [CC-BY-NC](https://creativecommons.org/licenses/by-nc/4.0/).
However, most of this project are available under a separate license terms: all codes used or modified from [StyleGAN3](https://github.com/NVlabs/stylegan3) is under the [Nvidia Source Code License](https://github.com/NVlabs/stylegan3/blob/main/LICENSE.txt).

Any form of use and derivative of this code must preserve the watermarking functionality showing "AI Generated".

## BibTeX

```bibtex
@inproceedings{pan2023draggan,
    title={Drag Your GAN: Interactive Point-based Manipulation on the Generative Image Manifold},
    author={Pan, Xingang and Tewari, Ayush, and Leimk{\"u}hler, Thomas and Liu, Lingjie and Meka, Abhimitra and Theobalt, Christian},
    booktitle = {ACM SIGGRAPH 2023 Conference Proceedings},
    year={2023}
}
```