# NVlabs/imaginaire

NVIDIA's Deep Imagination Team's PyTorch Library

Repository: https://github.com/NVlabs/imaginaire
Canonical: https://ross.abutalabs.com/products/imaginaire
Language: Python
License: NOASSERTION
License Family: other
Last push: 2022-11-29T10:24:50+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": 2241, "days_push": 1373, "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 4082, forks 446 (observed 2026-08-28T04:08:34.440236+00:00)

## What it is
NVIDIA's PyTorch library containing optimized implementations of image and video synthesis methods, including GAN-based image-to-image translation models like pix2pixHD, SPADE, UNIT, MUNIT, and FUNIT. It provides tutorials and a model zoo for training and running these generative models.

## Use cases
- translate semantic label maps into photorealistic images
- train pix2pixHD or SPADE for high-resolution image synthesis
- perform unsupervised image-to-image translation between domains
- generate images in unseen styles with few-shot learning
- reproduce NVIDIA GAN research papers in PyTorch
- run image and video synthesis models on GPUs

## When to choose
- you want reference PyTorch implementations of NVIDIA's GAN translation models
- you need high-resolution image-to-image translation with semantic layouts
- you are doing research on image or video synthesis

## When to avoid
- you need a general-purpose computer vision toolkit rather than generative synthesis models
- you require a permissive open-source license for commercial use
- you need actively maintained code with recent updates

## Facets
- artifact type: library
- maturity: maintenance
- function: machine-learning, image-processing, video-processing, deep-learning
- domain: deep-learning, computer-vision, image-processing, machine-learning
- platform: python
- tags: pytorch, gan, image-to-image-translation, video-synthesis, generative-models, nvidia, gpu, linux

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

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:34.440236+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 2026-08-29T18:23:24.923101+00:00, confidence not recorded.
  - readme: https://github.com/NVlabs/imaginaire (fetched 2026-08-28T04:08:34.440236+00:00, sha 0bbe8ecb811c)
- Data as of 2026-08-30T08:39:29.467469+00:00.