# NVlabs/stylegan2

StyleGAN2 - Official TensorFlow Implementation

Repository: https://github.com/NVlabs/stylegan2
Canonical: https://ross.abutalabs.com/products/stylegan2
Homepage: http://arxiv.org/abs/1912.04958
Language: Python
License: NOASSERTION
License Family: other
Last push: 2024-05-18T15:55:42+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2472, "days_push": 837, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 11184, forks 2489 (observed 2026-08-28T04:10:46.320697+00:00)

## What it is
The official TensorFlow implementation of StyleGAN2, NVIDIA's improved style-based generative adversarial network for high-quality unconditional image synthesis. It includes training code, pre-trained networks, and tooling from the paper 'Analyzing and Improving the Image Quality of StyleGAN'.

## Use cases
- generate photorealistic faces with a GAN
- train a StyleGAN2 model on my own image dataset
- generate high-resolution images from latent vectors
- project real images into GAN latent space
- reproduce the StyleGAN2 paper results
- use pre-trained GAN networks for image synthesis research

## When to choose
- you need the original, paper-faithful StyleGAN2 implementation in TensorFlow
- you want to reproduce or build on the published research results
- you need the official pre-trained networks from NVIDIA

## When to avoid
- you prefer PyTorch - use StyleGAN2-ADA-PyTorch instead
- you need actively maintained code with modern dependency support
- you want a simple high-level API rather than research code
- you need permissive licensing for commercial use

## Facets
- artifact type: library
- maturity: maintenance
- function: machine-learning, deep-learning, image-processing, gpu-computing
- domain: deep-learning, computer-vision, image-processing, artificial-intelligence
- platform: python
- tags: gan, generative-models, tensorflow, stylegan, image-synthesis, research-code, nvidia, linux, gpu

## Member repositories
- NVlabs/stylegan2 (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:10:46.320697+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T17:16:42.835094+00:00, confidence not recorded.
  - readme: https://github.com/NVlabs/stylegan2 (fetched 2026-08-28T04:10:46.320697+00:00, sha 4775f0d50178)
  - homepage: http://arxiv.org/abs/1912.04958 (fetched 2026-08-29T08:15:16.073918+00:00, sha b7481798b1ae)
  - site_page: https://info.arxiv.org/about/donate.html (fetched 2026-08-29T08:15:16.077730+00:00, sha cca9c3a11c56)
  - site_page: https://info.arxiv.org/about/ourmembers.html (fetched 2026-08-29T08:15:16.081280+00:00, sha 47cbc55ff1de)
  - site_page: https://info.arxiv.org/about (fetched 2026-08-29T08:15:16.084016+00:00, sha a1f16f915a9a)
  - site_page: https://info.arxiv.org/labs/index.html (fetched 2026-08-29T08:15:16.079581+00:00, sha b14a8d05a0ec)
- Data as of 2026-08-30T08:39:29.467469+00:00.