XingangPan/DragGAN
Official Code for DragGAN (SIGGRAPH 2023)
From the publisher
README & documentation
Source previewRead the project’s overview, installation instructions and usage examples. The original README is the source of truth.
Drag Your GAN: Interactive Point-based Manipulation on the Generative Image Manifold SIGGRAPH 2023 Conference Proceedings [](https://openxlab.org.cn/apps/detail/XingangPan/DragGAN) If you have CUDA graphic card, please follow the requirements of NVlabs/stylegan3. The usual installation steps involve the following commands, they should set up the correct CUDA version and all the python packages Then install the additional requirements Otherwise (for GPU acceleration on MacOS with Silicon Mac M1/M2, or just CPU) try the following: Provided docker image is based on NGC PyTorch repository. To quickly try out visualizer in Docker, run the following: Now you can open a shared link from Gradio (printed in the terminal console). Beware the Docker image takes about 25GB of disk space! To download pre-trained weights, simply run: If you want to try StyleGAN-Human and the Landscapes HQ (LHQ) dataset, please download weights from these links: StyleGAN-Human, LHQ, and put them under ./checkpoints. Feel free to try other pretrained…
Read the full README ↗ · Preview checked 2026-10-31T19:40:26.742Z
Inside the original README — Document outline
- Web Demos
- Requirements
- Run Gradio visualizer in Docker
- Download pre-trained StyleGAN2 weights
- Run DragGAN GUI
- Acknowledgement
- License
- BibTeX
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What this repository does
Official Code for DragGAN (SIGGRAPH 2023)
Repository facts
- Owner
- XingangPan
- Primary language
- Python
- Stars
- 35,710
- Forks
- 3,382
- Open issues + pull requests
- 154
- License
- Other
- Archived
- No
- Default branch
- main
- Created
- 2023-05-18T10:08:02.000Z
- Last push
- 2024-05-18T17:51:40.000Z
Topics and intended use
Owner-supplied topics: artificial-intelligence, generative-adversarial-network, generative-models, image-manipulation
Review the README for scope, installation, examples and limitations. We do not run repository code or certify it.
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Source and freshness
Source: GitHub. Metadata observed 2026-11-01T13:20:54.848Z. Daily imports are snapshots, not real-time monitoring.
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