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# Stable Diffusion web UI
A browser interface based on Gradio library for Stable Diffusion.
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![](screenshot.png)
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## Features
[Detailed feature showcase with images ](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Features ):
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- Original txt2img and img2img modes
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- One click install and run script (but you still must install python and git)
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- Outpainting
- Inpainting
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- Color Sketch
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- Prompt Matrix
- Stable Diffusion Upscale
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- Attention, specify parts of text that the model should pay more attention to
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- a man in a ((tuxedo)) - will pay more attention to tuxedo
- a man in a (tuxedo:1.21) - alternative syntax
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- select text and press ctrl+up or ctrl+down to automatically adjust attention to selected text (code contributed by anonymous user)
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- Loopback, run img2img processing multiple times
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- X/Y plot, a way to draw a 2 dimensional plot of images with different parameters
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- Textual Inversion
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- 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
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- train embeddings on 8GB (also reports of 6GB working)
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- Extras tab with:
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- GFPGAN, neural network that fixes faces
- CodeFormer, face restoration tool as an alternative to GFPGAN
- RealESRGAN, neural network upscaler
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- ESRGAN, neural network upscaler with a lot of third party models
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- SwinIR and Swin2SR([see here](https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/2092)), neural network upscalers
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- LDSR, Latent diffusion super resolution upscaling
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- Resizing aspect ratio options
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- Sampling method selection
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- Adjust sampler eta values (noise multiplier)
- More advanced noise setting options
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- Interrupt processing at any time
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- 4GB video card support (also reports of 2GB working)
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- Correct seeds for batches
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- Live prompt token length validation
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- 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
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- drag and drop an image/text-parameters to promptbox
- Read Generation Parameters Button, loads parameters in promptbox to UI
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- Settings page
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- Running arbitrary python code from UI (must run with --allow-code to enable)
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- Mouseover hints for most UI elements
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- Possible to change defaults/mix/max/step values for UI elements via text config
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- Random artist button
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- Tiling support, a checkbox to create images that can be tiled like textures
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- Progress bar and live image generation preview
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- 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
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- Img2img Alternative, reverse Euler method of cross attention control
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- Highres Fix, a convenience option to produce high resolution pictures in one click without usual distortions
- Reloading checkpoints on the fly
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- Checkpoint Merger, a tab that allows you to merge up to 3 checkpoints into one
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- [Custom scripts ](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Custom-Scripts ) with many extensions from community
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- [Composable-Diffusion ](https://energy-based-model.github.io/Compositional-Visual-Generation-with-Composable-Diffusion-Models/ ), a way to use multiple prompts at once
- separate prompts using uppercase `AND`
- also supports weights for prompts: `a cat :1.2 AND a dog AND a penguin :2.2`
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- No token limit for prompts (original stable diffusion lets you use up to 75 tokens)
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- DeepDanbooru integration, creates danbooru style tags for anime prompts
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- [xformers ](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Xformers ), major speed increase for select cards: (add --xformers to commandline args)
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- via extension: [History tab ](https://github.com/yfszzx/stable-diffusion-webui-images-browser ): view, direct and delete images conveniently within the UI
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- Generate forever option
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- Training tab
- hypernetworks and embeddings options
- Preprocessing images: cropping, mirroring, autotagging using BLIP or deepdanbooru (for anime)
- Clip skip
- Use Hypernetworks
- Use VAEs
- Estimated completion time in progress bar
- API
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- Support for dedicated [inpainting model ](https://github.com/runwayml/stable-diffusion#inpainting-with-stable-diffusion ) by RunwayML.
- via extension: [Aesthetic Gradients ](https://github.com/AUTOMATIC1111/stable-diffusion-webui-aesthetic-gradients ), a way to generate images with a specific aesthetic by using clip images embeds (implementation of [https://github.com/vicgalle/stable-diffusion-aesthetic-gradients ](https://github.com/vicgalle/stable-diffusion-aesthetic-gradients ))
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- [Stable Diffusion 2.0 ](https://github.com/Stability-AI/stablediffusion ) support - see [wiki ](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Features#stable-diffusion-20 ) for instructions
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## Installation and Running
Make sure the required [dependencies ](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Dependencies ) are met and follow the instructions available for both [NVidia ](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-NVidia-GPUs ) (recommended) and [AMD ](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-AMD-GPUs ) GPUs.
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Alternatively, use online services (like Google Colab):
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- [List of Online Services ](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Online-Services )
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### Automatic Installation on Windows
1. Install [Python 3.10.6 ](https://www.python.org/downloads/windows/ ), checking "Add Python to PATH"
2. Install [git ](https://git-scm.com/download/win ).
3. Download the stable-diffusion-webui repository, for example by running `git clone https://github.com/AUTOMATIC1111/stable-diffusion-webui.git` .
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4. Place stable diffusion checkpoint (`model.ckpt`) in the `models/Stable-diffusion` directory (see [dependencies ](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Dependencies ) for where to get it).
5. Run `webui-user.bat` from Windows Explorer as normal, non-administrator, user.
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### Automatic Installation on Linux
1. Install the dependencies:
```bash
# Debian-based:
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sudo apt install wget git python3 python3-venv
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# Red Hat-based:
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sudo dnf install wget git python3
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# Arch-based:
sudo pacman -S wget git python3
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```
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2. To install in `/home/$(whoami)/stable-diffusion-webui/` , run:
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```bash
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bash < (wget -qO- https://raw.githubusercontent.com/AUTOMATIC1111/stable-diffusion-webui/master/webui.sh)
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```
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### Installation on Apple Silicon
Find the instructions [here ](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Installation-on-Apple-Silicon ).
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## Contributing
Here's how to add code to this repo: [Contributing ](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Contributing )
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## Documentation
The documentation was moved from this README over to the project's [wiki ](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki ).
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## Credits
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Licenses for borrowed code can be found in `Settings -> Licenses` screen, and also in `html/licenses.html` file.
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- Stable Diffusion - https://github.com/CompVis/stable-diffusion, https://github.com/CompVis/taming-transformers
- k-diffusion - https://github.com/crowsonkb/k-diffusion.git
- GFPGAN - https://github.com/TencentARC/GFPGAN.git
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- CodeFormer - https://github.com/sczhou/CodeFormer
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- ESRGAN - https://github.com/xinntao/ESRGAN
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- SwinIR - https://github.com/JingyunLiang/SwinIR
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- Swin2SR - https://github.com/mv-lab/swin2sr
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- LDSR - https://github.com/Hafiidz/latent-diffusion
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- MiDaS - https://github.com/isl-org/MiDaS
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- Ideas for optimizations - https://github.com/basujindal/stable-diffusion
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- Cross Attention layer optimization - Doggettx - https://github.com/Doggettx/stable-diffusion, original idea for prompt editing.
- Cross Attention layer optimization - InvokeAI, lstein - https://github.com/invoke-ai/InvokeAI (originally http://github.com/lstein/stable-diffusion)
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- Sub-quadratic Cross Attention layer optimization - Alex Birch (https://github.com/Birch-san/diffusers/pull/1), Amin Rezaei (https://github.com/AminRezaei0x443/memory-efficient-attention)
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- Textual Inversion - Rinon Gal - https://github.com/rinongal/textual_inversion (we're not using his code, but we are using his ideas).
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- Idea for SD upscale - https://github.com/jquesnelle/txt2imghd
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- Noise generation for outpainting mk2 - https://github.com/parlance-zz/g-diffuser-bot
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- CLIP interrogator idea and borrowing some code - https://github.com/pharmapsychotic/clip-interrogator
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- Idea for Composable Diffusion - https://github.com/energy-based-model/Compositional-Visual-Generation-with-Composable-Diffusion-Models-PyTorch
- xformers - https://github.com/facebookresearch/xformers
- DeepDanbooru - interrogator for anime diffusers https://github.com/KichangKim/DeepDanbooru
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- Security advice - RyotaK
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- Initial Gradio script - posted on 4chan by an Anonymous user. Thank you Anonymous user.
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- (You)