# modelscope/facechain

FaceChain is a deep-learning toolchain for generating your Digital-Twin.

Repository: https://github.com/modelscope/facechain
Canonical: https://ross.abutalabs.com/products/facechain
Language: Jupyter Notebook
License: Apache-2.0
License Family: permissive
Last push: 2025-06-06T09:32:00+00:00

## Health v2 (maintenance only)
Score: 30/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 25, release rhythm 8, longevity 79
- inputs: {"age_days": 1119, "days_push": 453, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 9508, forks 873 (observed 2026-08-28T04:10:31.565104+00:00)

## What it is
FaceChain is a deep-learning toolchain from ModelScope for generating identity-preserved personal portraits (digital twins) from a single photo in seconds. It supports text-to-image and inpainting pipelines, integrates with ControlNet and LoRAs, and can be used via Python scripts, a Gradio interface, or SD WebUI.

## Use cases
- generate personal portrait photos in different styles from one selfie
- create a digital twin avatar of myself
- identity-preserving portrait generation with stable diffusion
- run face-adapted text-to-image with ControlNet and LoRA support
- train custom portrait style LoRAs
- generate AI avatars for profile pictures

## When to choose
- you need fast, identity-preserving portrait generation from a single photo
- you want compatibility with existing Stable Diffusion LoRAs and ControlNets
- you want both Python API and Gradio/WebUI interfaces

## When to avoid
- you need general-purpose image editing unrelated to human portraits
- you lack a GPU or cannot run diffusion models locally
- you need a fully hosted no-setup solution without any model downloads

## Facets
- artifact type: library
- maturity: active
- function: deep-learning, image-processing, machine-learning
- domain: artificial-intelligence, image-processing, deep-learning
- platform: python, cross-platform
- tags: portrait-generation, digital-twin, text-to-image, stable-diffusion, controlnet, lora, gradio, face-adapter, gpu

## Member repositories
- modelscope/facechain (main) score 30

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:10:31.565104+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 2026-08-29T17:22:00.704151+00:00, confidence not recorded.
  - readme: https://github.com/modelscope/facechain (fetched 2026-08-28T04:10:31.565104+00:00, sha 809b1da48cca)
- Data as of 2026-08-30T08:39:29.467469+00:00.