OpenGVLab/DragGAN
Unofficial Implementation of DragGAN - "Drag Your GAN: Interactive Point-based Manipulation on the Generative Image Manifold" （DragGAN 全功能实现，在线Demo，本地部署试用，代码、模型已全部开源，支持Windows, macOS, Linux） observed · 2026-08-28
Health v2 · maintenance only
29/100
- Activity 0
- Release rhythm 35
- Longevity 85
Flags: no_releases no_license
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 1201
- days_rel: n/a
- days_push: 1143
- n_releases_24m: 0
Adoption not part of the score
4946 stars · 473 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded
An unofficial full-featured Python implementation of DragGAN, the interactive point-based image manipulation method built on StyleGAN generative models. It provides a Gradio web demo, PyPI package, and local deployment on Windows, macOS, and Linux with open-source code and models.
Use cases
- drag points on a generated image to deform a face or animal pose
- edit GAN-generated images interactively in a browser demo
- run DragGAN locally with a GPU on Windows, macOS, or Linux
- invert a custom photo into a GAN latent and manipulate it
- try StyleGAN2-ada models for higher-quality image editing
- experiment with the Drag Your GAN paper's algorithm in Python
When to choose
- you want a ready-to-run DragGAN demo with online Colab and Gradio UI
- you need cross-platform local deployment via pip install
- you want to explore interactive point-based GAN image manipulation
When to avoid
- you need the official reference implementation (XingangPan/DragGAN)
- you require a maintained project with a license or active development
- you need reliable editing of arbitrary real photos (GAN inversion is limited)
Facets
application · maturity maintenance
image-processing machine-learning gui image-processing machine-learning graphics python windows draggan gan stylegan2 image-editing gradio generative-models unofficial-implementation linux macos docker
1 source
- readme: https://github.com/OpenGVLab/DragGAN · fetched 2026-08-28 · 0cf25e789d92
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| OpenGVLab/DragGAN | main | 29 |
For agents
markdown · JSON · MCP: product_card(name="OpenGVLab/DragGAN")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem