# bloc97/CrossAttentionControl

Unofficial implementation of "Prompt-to-Prompt Image Editing with Cross Attention Control" with Stable Diffusion

Repository: https://github.com/bloc97/CrossAttentionControl
Canonical: https://ross.abutalabs.com/products/crossattentioncontrol
Language: Jupyter Notebook
License: MIT
License Family: permissive
Topics: cross-attention, deep-learning, diffusion-models, stable-diffusion
Last push: 2022-10-18T15:50:28+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": 1454, "days_push": 1415, "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 1337, forks 83 (observed 2026-08-28T04:04:25.562986+00:00)

## What it is
An unofficial Jupyter Notebook implementation of the 'Prompt-to-Prompt Image Editing with Cross Attention Control' paper adapted for Stable Diffusion. It enables fine-grained prompt-based image editing by modifying internal attention maps during inference, without masks or model fine-tuning.

## Use cases
- edit stable diffusion images by changing prompt words without masks
- swap objects or attributes in AI-generated images
- perform image inversion to edit existing photos with stable diffusion
- control diffusion model output via cross attention maps
- reproduce prompt-to-prompt paper results on stable diffusion

## When to choose
- you want mask-free prompt-based editing of Stable Diffusion images
- you want to edit existing images via DDIM inversion with cross attention control
- you prefer a notebook-based research implementation you can modify

## When to avoid
- you need a maintained library compatible with recent diffusers versions
- you need a production-ready tool with a stable API
- you want plug-and-play image editing without running notebooks

## Facets
- artifact type: library
- maturity: maintenance
- function: image-processing, machine-learning, deep-learning
- domain: image-processing, artificial-intelligence, deep-learning
- platform: python
- tags: stable-diffusion, diffusion-models, cross-attention, prompt-to-prompt, image-editing, image-inversion, jupyter-notebook, diffusers, gpu

## Member repositories
- bloc97/CrossAttentionControl (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:25.562986+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 2026-08-30T04:44:02.350967+00:00, confidence not recorded.
  - readme: https://github.com/bloc97/CrossAttentionControl (fetched 2026-08-28T04:04:25.562986+00:00, sha 99c2926830ec)
- Data as of 2026-08-30T08:39:29.467469+00:00.