| # Stable Diffusion web UI |
| A browser interface based on Gradio library for Stable Diffusion. |
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| ## 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 |
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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/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. |
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| ### 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 |
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| 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 |
| 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 |
| - 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) |
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