# pix2pixzero/pix2pix-zero

Zero-shot Image-to-Image Translation  [SIGGRAPH 2023]

Repository: https://github.com/pix2pixzero/pix2pix-zero
Canonical: https://ross.abutalabs.com/products/pix2pix-zero
Homepage: https://pix2pixzero.github.io/
Language: Python
License: MIT
License Family: permissive
Last push: 2024-10-16T20:29:57+00:00

## Health v2 (maintenance only)
Score: 31/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 93
- inputs: {"age_days": 1304, "days_push": 686, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1146, forks 84 (observed 2026-08-28T04:03:45.737149+00:00)

## What it is
pix2pix-zero is a Python library implementing zero-shot image-to-image translation using pre-trained Stable Diffusion models. It enables editing real and synthetic images (e.g., cat to dog) without fine-tuning or manual text prompting, preserving input structure via cross-attention guidance.

## Use cases
- translate a photo of a cat into a dog without retraining a model
- edit real images with stable diffusion without writing text prompts
- apply style edits like low-poly or watercolor to photos
- convert horse images to zebras preserving structure
- run zero-shot image editing locally with diffusers
- reproduce SIGGRAPH 2023 image-to-image translation research

## When to choose
- you need training-free, prompt-free image editing with structure preservation
- you want to build on pre-trained Stable Diffusion via the diffusers library
- you are reproducing or extending the pix2pix-zero research

## When to avoid
- you need actively maintained production software with frequent updates
- you lack a GPU or cannot run large diffusion models locally
- you need text-prompt-driven editing rather than fixed edit directions

## Facets
- artifact type: library
- maturity: maintenance
- function: image-processing, machine-learning, deep-learning
- domain: image-processing, artificial-intelligence, computer-vision
- platform: python, cross-platform
- tags: stable-diffusion, image-to-image, diffusion-models, zero-shot, siggraph, research-code, gpu

## Member repositories
- pix2pixzero/pix2pix-zero (main) score 31

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:45.737149+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 2026-08-30T06:34:11.706084+00:00, confidence not recorded.
  - readme: https://github.com/pix2pixzero/pix2pix-zero (fetched 2026-08-28T04:03:45.737149+00:00, sha 725eac5a9c31)
  - homepage: https://pix2pixzero.github.io/ (fetched 2026-08-29T12:39:30.744169+00:00, sha 62777372ee7b)
- Data as of 2026-08-30T08:39:29.467469+00:00.