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automatic1111/stable-diffusion-webui

★ 162,744PythonAudience · vibe coderComplexity · 3/5MaintainedLicenseSetup · hard

TLDR

Browser-based interface for generating and editing images locally using Stable Diffusion AI, with text-to-image, image editing, upscaling, and training tools all in one web app.

Mindmap

mindmap
  root((repo))
    What it does
      Text to image
      Image editing
      Face restoration
      Photo upscaling
    Core features
      Outpainting inpainting
      Prompt weighting
      Batch processing
      Seed control
    Training tools
      Textual inversion
      Hypernetworks
      LoRA training
      Auto-tagging
    Tech stack
      Python
      Gradio
      PyTorch
      Multiple hardware
    Use cases
      Local image generation
      Batch photo editing
      Model fine-tuning
      Custom workflows

Things people build with this

USE CASE 1

Generate custom images from text descriptions without paying for a cloud service.

USE CASE 2

Edit and enhance photos locally, upscale, restore faces, extend scenes, with full control over parameters.

USE CASE 3

Train custom AI models on your own images using textual inversion or LoRA to generate specific styles or subjects.

USE CASE 4

Batch process hundreds of images with consistent settings and automate image tagging for organization.

Tech stack

PythonGradioPyTorchGFPGANRealESRGANESRGAN

Getting it running

Difficulty · hard Time to first run · 1day+

Requires GPU/CUDA, large model downloads (several GB), and PyTorch compilation; CPU-only is impractical.

Use freely for any purpose, including commercial use, as long as you keep the copyright notice and license text.

In plain English

Stable Diffusion web UI is a browser-based interface for Stable Diffusion, an AI image-generation model. It lets you type a text prompt and get back an image, edit existing images, restore faces, upscale photos, and many other image tasks, all from a single web page running on your own computer instead of a paid service. The interface is built with the Gradio library and exposes the underlying model through a long list of features. The two core modes are txt2img (turn text into a picture) and img2img (start from an existing picture and modify it). On top of that there is outpainting and inpainting (extending or repainting parts of an image), prompt attention syntax that lets you weight specific words, a negative-prompt field for things you do not want to see, styles you can save and reuse, and tools for variations, seed control, prompt editing mid-generation, and batch processing of many files. The Extras tab bundles face-restoration tools like GFPGAN and CodeFormer and upscalers like RealESRGAN, ESRGAN, SwinIR, and LDSR. Training features cover textual inversion embeddings, hypernetworks, and Loras, plus image preprocessing with BLIP or DeepDanbooru autotagging. There is also a checkpoint merger, an API, support for safetensors checkpoints, and many community-contributed custom scripts and extensions. You would use this when you want to generate or edit images locally with full control over models, samplers, and parameters rather than relying on a hosted service. The project is written in Python, can run on as little as 4GB of video memory, and supports NVidia, AMD, Intel, and Ascend hardware. The full README is longer than what was provided.

Copy-paste prompts

Prompt 1
How do I install and run Stable Diffusion web UI on my computer with an RTX 3060?
Prompt 2
Show me how to use the img2img feature to modify an existing photo and inpaint specific areas.
Prompt 3
What's the syntax for weighting words in prompts, and how do I use negative prompts to avoid unwanted elements?
Prompt 4
Walk me through training a custom LoRA model on my own image dataset using this web UI.
Prompt 5
How do I set up custom extensions and scripts in Stable Diffusion web UI to automate batch image processing?
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Generated 2026-05-21 · Model: sonnet-4-6 · Verify against the repo before relying on details.