DragGAN

💥 Colab Demo | InternGPT Free Online Demo

pip install draggan

An out-of-box online demo is integrated in InternGPT - a super cool pointing-language-driven visual interactive system. Enjoy for free.:lollipop:

Note for Colab, remember to select a GPU via Runtime/Change runtime type (代码执行程序/更改运行时类型).

Unofficial implementation of Drag Your GAN: Interactive Point-based Manipulation on the Generative Image Manifold

News

🌟 What's New

• [2023/5/25] DragGAN is on PyPI, simple install via pip install draggan. Also addressed the common CUDA problems OpenGVLab#38 OpenGVLab#12
• [2023/5/25] We now support StyleGAN2-ada with much higher quality and more types of images. Try it by selecting models started with "ada".
• [2023/5/24] Custom Image with GAN inversion is supported, but it is possible that your custom images are distorted due to the limitation of GAN inversion. Besides, it is also possible the manipulations fail due to the limitation of our implementation.

🌟 Changelog

• Tweak performance.
• Improving installation experience, DragGAN is now on PyPI.
• Automatically determining the number of iterations.
• Support StyleGAN2-ada.
• Integrate into InternGPT
• Custom Image with GAN inversion.
• Download generated image and generation trajectory.
• Controlling generation process with GUI.
• Automatically download stylegan2 checkpoint.
• Support movable region, multiple handle points.
• Gradio and Colab Demo.

This project is now a sub-project of InternGPT for interactive image editing. Future updates of more cool tools beyond DragGAN would be added in InternGPT.

How it Work ?

Check out the original paper for the backend algorithm and math.

Here is a simple tutorial video showing how to use our implementation.

demo.mp4

Running Locally

With PyPI

conda create -n draggan python=3.7
conda activate draggan
pip install draggan

Launch the Gradio demo

python -m draggan.web

Clone and Install

Ensure you have a GPU and CUDA installed. We use Python 3.7 for testing, other versions (>= 3.7) of Python should work too, but not tested. We recommend to use Conda to prepare all the requirements.

For Windows users, you might encounter some issues caused by StyleGAN custom ops, youd could find some solutions from the issues pannel. We are also working on a more friendly package without setup.

git clone https://github.com/Zeqiang-Lai/DragGAN.git
cd DragGAN
conda create -n draggan python=3.7
conda activate draggan
pip install -r requirements.txt

Launch the Gradio demo

python gradio_app.py

If you have any issue for downloading the checkpoint, you could manually download it from here and put it into the folder checkpoints.

Acknowledgement

Official DragGAN   StyleGAN2   StyleGAN2-pytorch   StyleGAN2-Ada

Citation

@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}
}