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A browser interface based on Gradio library for Stable Diffusion.
aiai-artdeep-learningdiffusiongradioimage-generationimage2imageimg2imgpytorchstable-diffusiontext2imagetorchtxt2imgunstableupscalingweb
82eb8ea452
split vals not 's' from tests |
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.github/ISSUE_TEMPLATE | ||
embeddings | ||
javascript | ||
models/Stable-diffusion | ||
modules | ||
scripts | ||
textual_inversion_templates | ||
.gitignore | ||
artists.csv | ||
environment-wsl2.yaml | ||
launch.py | ||
README.md | ||
requirements_versions.txt | ||
requirements.txt | ||
screenshot.png | ||
script.js | ||
style.css | ||
txt2img_Screenshot.png | ||
webui-user.bat | ||
webui-user.sh | ||
webui.bat | ||
webui.py | ||
webui.sh |
Stable Diffusion web UI
A browser interface based on Gradio library for Stable Diffusion.
Check the custom scripts wiki page for extra scripts developed by users.
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
- 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
- Loopback, run img2img processing multiple times
- X/Y plot, a way to draw a 2 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
- 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, neural network upscaler
- LDSR, Latent diffusion super resolution upscaling
- Resizing aspect ratio options
- Sampling method selection
- Interrupt processing at any time
- 4GB video card support (also reports of 2GB working)
- Correct seeds for batches
- Prompt length validation
- get length of prompt in tokens as you type
- get a warning after generation if some text was truncated
- 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
- 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
- Random artist button
- Tiling support, a checkbox to create images that can be tiled like textures
- Progress bar and live image generation preview
- 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
- 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 two checkpoints into one
- Custom scripts with many extensions from community
Installation and Running
Make sure the required dependencies are met and follow the instructions available for both NVidia (recommended) and AMD GPUs.
Alternatively, use Google Colab:
Automatic Installation on Windows
- Install Python 3.10.6, checking "Add Python to PATH"
- Install git.
- Download the stable-diffusion-webui repository, for example by running
git clone https://github.com/AUTOMATIC1111/stable-diffusion-webui.git
. - Place
model.ckpt
in themodels
directory (see dependencies for where to get it). - (Optional) Place
GFPGANv1.4.pth
in the base directory, alongsidewebui.py
(see dependencies for where to get it). - Run
webui-user.bat
from Windows Explorer as normal, non-administrator, user.
Automatic Installation on Linux
- Install the dependencies:
# 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
- To install in
/home/$(whoami)/stable-diffusion-webui/
, run:
bash <(wget -qO- https://raw.githubusercontent.com/AUTOMATIC1111/stable-diffusion-webui/master/webui.sh)
Installation on Apple Silicon
Find the instructions here.
Contributing
Here's how to add code to this repo: Contributing
Documentation
The documentation was moved from this README over to the project's wiki.
Credits
- 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
- LDSR - https://github.com/Hafiidz/latent-diffusion
- Ideas for optimizations - https://github.com/basujindal/stable-diffusion
- Doggettx - Cross Attention layer optimization - https://github.com/Doggettx/stable-diffusion, original idea for prompt editing.
- Rinon Gal - Textual Inversion - 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
- Initial Gradio script - posted on 4chan by an Anonymous user. Thank you Anonymous user.
- (You)