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# Stable Diffusion web UI | |
A browser interface based on Gradio library for Stable Diffusion. | |
![](screenshot.png) | |
## Features | |
[Detailed feature showcase with images](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Features): | |
- 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 press `Ctrl+Up` or `Ctrl+Down` 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](https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/2092)), 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-code` to 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 scripts](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Custom-Scripts) with many extensions from community | |
- [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` | |
- 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](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Xformers), major speed increase for select cards: (add `--xformers` to commandline args) | |
- via extension: [History tab](https://github.com/yfszzx/stable-diffusion-webui-images-browser): 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 sparate 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 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)) | |
- [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 | |
- [Alt-Diffusion](https://arxiv.org/abs/2211.06679) support - see [wiki](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Features#alt-diffusion) for instructions | |
- Now without any bad letters! | |
- Load checkpoints in safetensors format | |
- Eased resolution restriction: generated image's domension must be a multiple of 8 rather than 64 | |
- Now with a license! | |
- Reorder elements in the UI from settings screen | |
## 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. | |
Alternatively, use online services (like Google Colab): | |
- [List of Online Services](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Online-Services) | |
### Automatic Installation on Windows | |
1. Install [Python 3.10.6](https://www.python.org/downloads/release/python-3106/) (Newer version of Python does not support torch), 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`. | |
4. Run `webui-user.bat` from Windows Explorer as normal, non-administrator, user. | |
### Automatic Installation on Linux | |
1. Install the dependencies: | |
```bash | |
# Debian-based: | |
sudo apt install wget git python3 python3-venv | |
# Red Hat-based: | |
sudo dnf install wget git python3 | |
# Arch-based: | |
sudo pacman -S wget git python3 | |
``` | |
2. Navigate to the directory you would like the webui to be installed and execute the following command: | |
```bash | |
bash <(wget -qO- https://raw.githubusercontent.com/AUTOMATIC1111/stable-diffusion-webui/master/webui.sh) | |
``` | |
3. Run `webui.sh`. | |
4. Check `webui-user.sh` for options. | |
### Installation on Apple Silicon | |
Find the instructions [here](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Installation-on-Apple-Silicon). | |
## Contributing | |
Here's how to add code to this repo: [Contributing](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Contributing) | |
## Documentation | |
The documentation was moved from this README over to the project's [wiki](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki). | |
## Credits | |
Licenses for borrowed code can be found in `Settings -> Licenses` screen, and also in `html/licenses.html` file. | |
- 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 | |
- CodeFormer - https://github.com/sczhou/CodeFormer | |
- ESRGAN - https://github.com/xinntao/ESRGAN | |
- SwinIR - https://github.com/JingyunLiang/SwinIR | |
- Swin2SR - https://github.com/mv-lab/swin2sr | |
- LDSR - https://github.com/Hafiidz/latent-diffusion | |
- MiDaS - https://github.com/isl-org/MiDaS | |
- Ideas for optimizations - https://github.com/basujindal/stable-diffusion | |
- 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) | |
- 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) | |
- Textual Inversion - Rinon Gal - https://github.com/rinongal/textual_inversion (we're not using his code, but we are using his ideas). | |
- Idea for SD upscale - https://github.com/jquesnelle/txt2imghd | |
- Noise generation for outpainting mk2 - https://github.com/parlance-zz/g-diffuser-bot | |
- CLIP interrogator idea and borrowing some code - https://github.com/pharmapsychotic/clip-interrogator | |
- 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 | |
- Sampling in float32 precision from a float16 UNet - marunine for the idea, Birch-san for the example Diffusers implementation (https://github.com/Birch-san/diffusers-play/tree/92feee6) | |
- Instruct pix2pix - Tim Brooks (star), Aleksander Holynski (star), Alexei A. Efros (no star) - https://github.com/timothybrooks/instruct-pix2pix | |
- Security advice - RyotaK | |
- UniPC sampler - Wenliang Zhao - https://github.com/wl-zhao/UniPC | |
- Initial Gradio script - posted on 4chan by an Anonymous user. Thank you Anonymous user. | |
- (You) | |