# FireRedTeam/FireRed-Image-Edit

FireRed-Image-Edit is a powerful image editing foundation model achieving open-source state-of-the-art performance with precise instruction following, high-fidelity generation, superior identity consistency, and seamless multi-element fusion.

Repository: https://github.com/FireRedTeam/FireRed-Image-Edit
Canonical: https://ross.abutalabs.com/products/firered-image-edit
Language: Python
License: Apache-2.0
License Family: permissive
Topics: aigc, deep-learning, diffusion-models, image-generation, image2image, pytorch
Last push: 2026-04-03T17:02:49+00:00

## Health v2 (maintenance only)
Score: 49/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 75, release rhythm 35, longevity 14
- inputs: {"age_days": 203, "days_push": 152, "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 1341, forks 79 (observed 2026-08-28T04:04:26.166045+00:00)

## What it is
FireRed-Image-Edit is an open-source image editing foundation model built on diffusion models, released as PyTorch model weights with inference code and a LoRA fine-tuning zoo. It achieves state-of-the-art instruction-based image editing with precise instruction following, high-fidelity generation, identity consistency, and multi-element fusion.

## Use cases
- edit photos with natural language instructions
- instruction-based image editing model
- change objects in an image while keeping identity consistent
- fuse multiple image elements into one picture
- fine-tune an image editing model with LoRA
- run a state-of-the-art open-source image2image diffusion model

## When to choose
- you need an open-source, instruction-following image editing model with high fidelity and identity consistency
- you want to fine-tune or adapt an image editing model via LoRA on your own data
- you need reproducible benchmarks for instruction-based image editing (REDEdit-Bench)
- your stack is Python/PyTorch with GPU resources available

## When to avoid
- you need a polished end-user photo editor GUI rather than a model and inference code
- you have no GPU or cannot run large diffusion models locally
- you need text-to-image generation from scratch rather than editing existing images
- you require a permissive setup without downloading large model weights from Hugging Face

## Facets
- artifact type: library
- maturity: active
- function: image-processing, machine-learning, deep-learning
- domain: image-processing, artificial-intelligence, deep-learning
- platform: python, cross-platform
- tags: diffusion-models, image-editing, image2image, instruction-following, aigc, pytorch, generative-ai, lora, model-weights, huggingface, gpu

## Member repositories
- FireRedTeam/FireRed-Image-Edit (main) score 49

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:26.166045+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 2026-08-30T04:43:43.094874+00:00, confidence not recorded.
  - readme: https://github.com/FireRedTeam/FireRed-Image-Edit (fetched 2026-08-28T04:04:26.166045+00:00, sha 6894e0dc17cd)
- Data as of 2026-08-30T08:39:29.467469+00:00.