Spaces:
Runtime error
Runtime error
| # Stable Diffusion web UI | |
| A browser interface based on Gradio library for Stable Diffusion. | |
|  | |
| ## 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` (or `Command+Up` or `Command+Down` if 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](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) | |
| ### Installation on Windows 10/11 with NVidia-GPUs using release package | |
| 1. Download `sd.webui.zip` from [v1.0.0-pre](https://github.com/AUTOMATIC1111/stable-diffusion-webui/releases/tag/v1.0.0-pre) and extract it's contents. | |
| 2. Run `update.bat`. | |
| 3. Run `run.bat`. | |
| > For more details see [Install-and-Run-on-NVidia-GPUs](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-NVidia-GPUs) | |
| ### 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 | |
| - TAESD - Ollin Boer Bohan - https://github.com/madebyollin/taesd | |
| - Initial Gradio script - posted on 4chan by an Anonymous user. Thank you Anonymous user. | |
| - (You) | |