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--- |
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title: DragGAN |
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app_file: visualizer_drag_gradio.py |
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sdk: gradio |
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sdk_version: 3.35.2 |
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--- |
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<p align="center"> |
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<h1 align="center">Drag Your GAN: Interactive Point-based Manipulation on the Generative Image Manifold</h1> |
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<p align="center"> |
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<a href="https://xingangpan.github.io/"><strong>Xingang Pan</strong></a> |
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路 |
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<a href="https://ayushtewari.com/"><strong>Ayush Tewari</strong></a> |
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路 |
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<a href="https://people.mpi-inf.mpg.de/~tleimkue/"><strong>Thomas Leimk眉hler</strong></a> |
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路 |
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<a href="https://lingjie0206.github.io/"><strong>Lingjie Liu</strong></a> |
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路 |
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<a href="https://www.meka.page/"><strong>Abhimitra Meka</strong></a> |
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路 |
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<a href="http://www.mpi-inf.mpg.de/~theobalt/"><strong>Christian Theobalt</strong></a> |
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</p> |
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<h2 align="center">SIGGRAPH 2023 Conference Proceedings</h2> |
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<div align="center"> |
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<img src="DragGAN.gif", width="600"> |
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</div> |
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<p align="center"> |
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<br> |
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<a href="https://pytorch.org/get-started/locally/"><img alt="PyTorch" src="https://img.shields.io/badge/PyTorch-ee4c2c?logo=pytorch&logoColor=white"></a> |
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<a href="https://twitter.com/XingangP"><img alt='Twitter' src="https://img.shields.io/twitter/follow/XingangP?label=%40XingangP"></a> |
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<a href="https://arxiv.org/abs/2305.10973"> |
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<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'> |
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</a> |
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<a href='https://vcai.mpi-inf.mpg.de/projects/DragGAN/'> |
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<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> |
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<a href="https://colab.research.google.com/drive/1mey-IXPwQC_qSthI5hO-LTX7QL4ivtPh?usp=sharing"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a> |
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</p> |
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</p> |
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## Web Demos |
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[](https://openxlab.org.cn/apps/detail/XingangPan/DragGAN) |
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<p align="left"> |
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<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> |
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</p> |
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## Requirements |
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If you have CUDA graphic card, please follow the requirements of [NVlabs/stylegan3](https://github.com/NVlabs/stylegan3#requirements). |
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Otherwise (for GPU acceleration on MacOS with Silicon Mac M1/M2, or just CPU) try the following: |
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```sh |
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cat environment.yml | \ |
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grep -v -E 'nvidia|cuda' > environment-no-nvidia.yml && \ |
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conda env create -f environment-no-nvidia.yml |
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conda activate stylegan3 |
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# On MacOS |
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export PYTORCH_ENABLE_MPS_FALLBACK=1 |
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``` |
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## Download pre-trained StyleGAN2 weights |
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To download pre-trained weights, simply run: |
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```sh |
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sh scripts/download_model.sh |
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``` |
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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`. |
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Feel free to try other pretrained StyleGAN. |
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## Run DragGAN GUI |
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To start the DragGAN GUI, simply run: |
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```sh |
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sh scripts/gui.sh |
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``` |
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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. |
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You can run DragGAN Gradio demo as well: |
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```sh |
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python visualizer_drag_gradio.py |
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``` |
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## Acknowledgement |
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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). |
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## License |
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The code related to the DragGAN algorithm is licensed under [CC-BY-NC](https://creativecommons.org/licenses/by-nc/4.0/). |
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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). |
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Any form of use and derivative of this code must preserve the watermarking functionality showing "AI Generated". |
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## BibTeX |
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```bibtex |
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@inproceedings{pan2023draggan, |
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title={Drag Your GAN: Interactive Point-based Manipulation on the Generative Image Manifold}, |
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author={Pan, Xingang and Tewari, Ayush, and Leimk{\"u}hler, Thomas and Liu, Lingjie and Meka, Abhimitra and Theobalt, Christian}, |
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booktitle = {ACM SIGGRAPH 2023 Conference Proceedings}, |
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year={2023} |
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} |
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``` |
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