# SUDO-AI-3D/zero123plus

Code repository for Zero123++: a Single Image to Consistent Multi-view Diffusion Base Model.

Repository: https://github.com/SUDO-AI-3D/zero123plus
Canonical: https://ross.abutalabs.com/products/zero123plus
Language: Python
License: Apache-2.0
License Family: permissive
Topics: 3d, 3d-graphics, aigc, diffusers, diffusion-models, image-to-3d, research-project, text-to-3d
Last push: 2024-02-23T18:17:53+00:00

## Health v2 (maintenance only)
Score: 27/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 75
- inputs: {"age_days": 1052, "days_push": 922, "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 2095, forks 148 (observed 2026-08-28T04:06:13.225362+00:00)

## What it is
Zero123++ is a diffusion base model that generates consistent multi-view images from a single input image, intended as a stepping stone for 3D asset generation. The repository provides a custom diffusers pipeline, example scripts, and a ControlNet normal-image generator for producing view-space normal maps and alpha masks.

## Use cases
- generate multiple consistent views of an object from one photo
- create 3D assets from a single image
- generate view-space normal maps for 3D reconstruction
- produce alpha masks for object matting
- novel view synthesis of objects
- build image-to-3d pipelines with diffusers

## When to choose
- you need multi-view image generation from a single image as input to 3D reconstruction
- you want a diffusers-compatible pipeline for image-to-3d research
- you need normal maps or alpha masks to support 3D generation workflows

## When to avoid
- you need a commercial-use license for the model weights (they are CC-BY-NC 4.0)
- you want text-to-image generation rather than single-image-to-multi-view
- you lack a GPU or PyTorch environment

## Facets
- artifact type: library
- maturity: active
- function: machine-learning, deep-learning, image-processing, stable-diffusion
- domain: artificial-intelligence, computer-vision, graphics, machine-learning
- platform: python
- tags: image-to-3d, multi-view-diffusion, diffusers, novel-view-synthesis, 3d-generation, research-project, gpu

## Member repositories
- SUDO-AI-3D/zero123plus (main) score 27

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:13.225362+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 2026-08-30T02:54:38.505837+00:00, confidence not recorded.
  - readme: https://github.com/SUDO-AI-3D/zero123plus (fetched 2026-08-28T04:06:13.225362+00:00, sha c81e8f415569)
- Data as of 2026-08-30T08:39:29.467469+00:00.