XingangPan/DragGAN

Health v2 · maintenance only

Flags: no_releases no_license

Adoption not part of the score

35755 stars · 3401 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Official PyTorch implementation of DragGAN (SIGGRAPH 2023), an interactive point-based image manipulation method built on StyleGAN3. Users drag handle points on a generated image to precisely control pose, shape, expression, and layout, with a Gradio visualizer and web demos included.

Use cases

• drag points on a generated image to change pose or expression
• edit GAN-generated images with precise pixel control
• research interactive GAN-based image manipulation
• run a demo of point-based image editing
• manipulate layout and shape of generated photos

When to choose

• you need the official, research-accurate implementation of DragGAN
• you want interactive point-based editing on a StyleGAN3 generative manifold
• you have a CUDA GPU or Apple Silicon for running the visualizer

When to avoid

• you need general-purpose photo editing of arbitrary real images rather than GAN-generated ones
• you lack a GPU and need fast interactive performance
• you need a permissively licensed production-ready library (license is non-standard)

Facets

library · maturity stable

image-processing machine-learning deep-learning artificial-intelligence computer-vision image-processing python windows gan stylegan3 image-manipulation interactive-editing pytorch siggraph-2023 research-code gradio generative-models gpu linux macos

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For agents

markdown · JSON · MCP: product_card(name="XingangPan/DragGAN")