Stable Diffusion web UI

A web interface for Stable Diffusion, implemented using Gradio library.

Features

Detailed feature showcase with images:

• Original txt2img and img2img modes
• One click install and run script (but you still must install Python and git)
• Outpainting
• Inpainting
• Color Sketch
• Prompt Matrix
• Stable Diffusion Upscale
• Attention, specify parts of text that the model should pay more attention to
  • a man in a((tuxedo))- will pay more attention to tuxedo
  • a man in a(tuxedo:1.21)- alternative syntax
  • select text and pressCtrl+UporCtrl+Down(orCommand+UporCommand+Downif you're on a MacOS) to automatically adjust attention to selected text (code contributed by anonymous user)
• Loopback, run img2img processing multiple times
• X/Y/Z plot, a way to draw a 3 dimensional plot of images with different parameters
• Textual Inversion
  • have as many embeddings as you want and use any names you like for them
  • use multiple embeddings with different numbers of vectors per token
  • works with half precision floating point numbers
  • train embeddings on 8GB (also reports of 6GB working)
• Extras tab with:
  • GFPGAN, neural network that fixes faces
  • CodeFormer, face restoration tool as an alternative to GFPGAN
  • RealESRGAN, neural network upscaler
  • ESRGAN, neural network upscaler with a lot of third party models
  • SwinIR and Swin2SR (see here), neural network upscalers
  • LDSR, Latent diffusion super resolution upscaling
• Resizing aspect ratio options
• Sampling method selection
  • Adjust sampler eta values (noise multiplier)
  • More advanced noise setting options
• Interrupt processing at any time
• 4GB video card support (also reports of 2GB working)
• Correct seeds for batches
• Live prompt token length validation
• Generation parameters
  • parameters you used to generate images are saved with that image
  • in PNG chunks for PNG, in EXIF for JPEG
  • can drag the image to PNG info tab to restore generation parameters and automatically copy them into UI
  • can be disabled in settings
  • drag and drop an image/text-parameters to promptbox
• Read Generation Parameters Button, loads parameters in promptbox to UI
• Settings page
• Running arbitrary Python code from UI (must run with--allow-codeto enable)
• Mouseover hints for most UI elements
• Possible to change defaults/mix/max/step values for UI elements via text config
• Tiling support, a checkbox to create images that can be tiled like textures
• Progress bar and live image generation preview
  • Can use a separate neural network to produce previews with almost none VRAM or compute requirement
• Negative prompt, an extra text field that allows you to list what you don't want to see in generated image
• Styles, a way to save part of prompt and easily apply them via dropdown later
• Variations, a way to generate same image but with tiny differences
• Seed resizing, a way to generate same image but at slightly different resolution
• CLIP interrogator, a button that tries to guess prompt from an image
• Prompt Editing, a way to change prompt mid-generation, say to start making a watermelon and switch to anime girl midway
• Batch Processing, process a group of files using img2img
• Img2img Alternative, reverse Euler method of cross attention control
• Highres Fix, a convenience option to produce high resolution pictures in one click without usual distortions
• Reloading checkpoints on the fly
• Checkpoint Merger, a tab that allows you to merge up to 3 checkpoints into one
• Custom scriptswith many extensions from community
• Composable-Diffusion,a way to use multiple prompts at once
  • separate prompts using uppercaseAND
  • also supports weights for prompts:a cat:1.2 AND a dog AND a penguin:2.2
• No token limit for prompts (original stable diffusion lets you use up to 75 tokens)
• DeepDanbooru integration, creates danbooru style tags for anime prompts
• xformers,major speed increase for select cards: (add--xformersto commandline args)
• via extension:History tab:view, direct and delete images conveniently within the UI
• Generate forever option
• Training tab
  • hypernetworks and embeddings options
  • Preprocessing images: cropping, mirroring, autotagging using BLIP or deepdanbooru (for anime)
• Clip skip
• Hypernetworks
• Loras (same as Hypernetworks but more pretty)
• A separate UI where you can choose, with preview, which embeddings, hypernetworks or Loras to add to your prompt
• Can select to load a different VAE from settings screen
• Estimated completion time in progress bar
• API
• Support for dedicatedinpainting modelby RunwayML
• via extension:Aesthetic Gradients,a way to generate images with a specific aesthetic by using clip images embeds (implementation ofhttps://github /vicgalle/stable-diffusion-aesthetic-gradients)
• Stable Diffusion 2.0support - seewikifor instructions
• Alt-Diffusionsupport - seewikifor instructions
• Now without any bad letters!
• Load checkpoints in safetensors format
• Eased resolution restriction: generated image's dimensions must be a multiple of 8 rather than 64
• Now with a license!
• Reorder elements in the UI from settings screen
• Segmind Stable Diffusionsupport

Installation and Running

Make sure the requireddependenciesare met and follow the instructions available for:

• NVidia(recommended)
• AMDGPUs.
• Intel CPUs, Intel GPUs (both integrated and discrete)(external wiki page)
• Ascend NPUs(external wiki page)

Alternatively, use online services (like Google Colab):

• List of Online Services

Installation on Windows 10/11 with NVidia-GPUs using release package

1. Downloadsd.webui.zipfromv1.0.0-preand extract its contents.
2. Runupdate.bat.
3. Runrun.bat.

For more details seeInstall-and-Run-on-NVidia-GPUs

Automatic Installation on Windows

1. InstallPython 3.10.6(Newer version of Python does not support torch), checking "Add Python to PATH".
2. Installgit.
3. Download the stable-diffusion-webui repository, for example by runninggit clone https://github /AUTOMATIC1111/stable-diffusion-webui.git.
4. Runwebui-user.batfrom Windows Explorer as normal, non-administrator, user.

Automatic Installation on Linux

1. Install the dependencies:

#Debian-based:
sudo apt install wget git Python 3 Python 3-venv libgl1 libglib2.0-0
#Red Hat-based:
sudo dnf install wget git Python 3 gperftools-libs libglvnd-glx
#openSUSE-based:
sudo zypper install wget git Python 3 libtcmalloc4 libglvnd
#Arch-based:
sudo pacman -S wget git Python 3

2. Navigate to the directory you would like the webui to be installed and execute the following command:

wget -q https://raw.githubusercontent /AUTOMATIC1111/stable-diffusion-webui/master/webui.sh

3. Runwebui.sh.
4. Checkwebui-user.shfor options.

Installation on Apple Silicon

Find the instructionshere.

Contributing

Here's how to add code to this repo:Contributing

Documentation

The documentation was moved from this README over to the project'swiki.

For the purposes of getting Google and other search engines to crawl the wiki, here's a link to the (not for humans)crawlable wiki.

Credits

Licenses for borrowed code can be found inSettings -> Licensesscreen, and also inhtml/licenses.htmlfile.

• Stable Diffusion -https://github /Stability-AI/stablediffusion,https://github /CompVis/taming-transformers
• k-diffusion -https://github /crowsonkb/k-diffusion.git
• Spandrel -https://github /chaiNNer-org/spandrelimplementing
  • GFPGAN -https://github /TencentARC/GFPGAN.git
  • CodeFormer -https://github /sczhou/CodeFormer
  • ESRGAN -https://github /xinntao/ESRGAN
  • SwinIR -https://github /JingyunLiang/SwinIR
  • Swin2SR -https://github /mv-lab/swin2sr
• LDSR -https://github /Hafiidz/latent-diffusion
• MiDaS -https://github /isl-org/MiDaS
• Ideas for optimizations -https://github /basujindal/stable-diffusion
• Cross Attention layer optimization - Doggettx -https://github /Doggettx/stable-diffusion,original idea for prompt editing.
• Cross Attention layer optimization - InvokeAI, lstein -https://github /invoke-ai/InvokeAI(originallyhttp://github /lstein/stable-diffusion)
• Sub-quadratic Cross Attention layer optimization - Alex Birch (Birch-san/diffusers#1), Amin Rezaei (https://github /AminRezaei0x443/memory-efficient-attention)
• Textual Inversion - Rinon Gal -https://github /rinongal/textual_inversion(we're not using his code, but we are using his ideas).
• Idea for SD upscale -https://github /jquesnelle/txt2imghd
• Noise generation for outpainting mk2 -https://github /parlance-zz/g-diffuser-bot
• CLIP interrogator idea and borrowing some code -https://github /pharmapsychotic/clip-interrogator
• Idea for Composable Diffusion -https://github /energy-based-model/Compositional-Visual-Generation-with-Composable-Diffusion-Models-PyTorch
• xformers -https://github /facebookresearch/xformers
• DeepDanbooru - interrogator for anime diffusershttps://github /KichangKim/DeepDanbooru
• Sampling in float32 precision from a float16 UNet - marunine for the idea, Birch-san for the example Diffusers implementation (https://github /Birch-san/diffusers-play/tree/92feee6)
• Instruct pix2pix - Tim Brooks (star), Aleksander Holynski (star), Alexei A. Efros (no star) -https://github /timothybrooks/instruct-pix2pix
• Security advice - RyotaK
• UniPC sampler - Wenliang Zhao -https://github /wl-zhao/UniPC
• TAESD - Ollin Boer Bohan -https://github /madebyollin/taesd
• LyCORIS - KohakuBlueleaf
• Restart sampling - lambertae -https://github /Newbeeer/diffusion_restart_sampling
• Hypertile - tfernd -https://github /tfernd/HyperTile
• Initial Gradio script - posted on 4chan by an Anonymous user. Thank you Anonymous user.
• (You)