Heavily opinionated custom fork of https://github.com/AUTOMATIC1111/stable-diffusion-webui

Fork is as close as up-to-date with origin as time allows
All code changes are merged upstream whenever possible

The idea behind the fork is to enable latest technologies and advances in text-to-image generation
Sometimes this is not the same as "as simple as possible to use"
If you are looking an amazing simple-to-use Stable Diffusion tool, I'd suggest InvokeAI specifically due to its automated installer and ease of use

• New logger
• New error and exception handlers
• Built-in performance profiler
• Enhanced environment tuning
• Updated libraries to latest known compatible versions
• Includes opinionated System and Options configuration
• Does not rely on Accelerate as it only affects distributed systems
• Optimized startup
  Gradio web server will be initialized much earlier which model load is done in the background
  Faster model loading plus ability to fallback on corrupt models
• Uses simplified folder structure
  e.g. /train, /outputs/*, /models/*, etc.
• Enhanced training templates
• Built-in LoRA, LyCORIS, Custom Diffusion, Dreambooth training
• Majority of settings configurable via UI without the need for command line flags
  e.g, cross-optimization methods, system folders, etc.

• Includes updated UI: reskinned and reorganized
  Black and orange dark theme with fixed width options panels and larger previews

• Optimized for Torch 2.0
• Runs with SDP memory attention enabled by default if supported by system
• Auto-adjust parameters when running on CPU or CUDA
  Note: AMD and M1 platforms are supported, but without out-of-the-box optimizations

• Drops compatibility with older versions of python and requires 3.9 or 3.10
• Drops localizations
• Drops automated tests

Fork adds extra functionality:

• New skin and UI layout
• Ships with set of CLI tools that rely on SD API for execution:
  e.g. generate, train, bench, etc.
  Full list

• System Info
• ControlNet
• Image Browser
• LORA (both training and inference)
• LyCORIS (both training and inference)
• Model Converter
• CLiP Interrogator
• Dynamic Thresholding
• Steps Animation
• Seed Travel
• Model Keyword

1. Install first:
   Python & Git
2. If you have nVidia GPU, install nVidia CUDA toolkit:
   https://developer.nvidia.com/cuda-downloads
3. Clone repository
   git clone https://github.com/vladmandic/automatic

Run desired startup script to install dependencies and extensions and start server:

• webui.bat and webui.sh:
  Platform specific wrapper scripts For Windows, Linux and OSX
  Starts launch.py in a Python virtual environment (venv)
  Note: Server can run without virtual environment, but it is recommended to use it to avoid library version conflicts with other applications
  If you're unsure which launcher to use, this is the one you want
• launch.py:
  Main startup script
  Can be used directly to start server in a manually activated venv or to run server without venv
• setup.py:
  Main installer, used by launch.py
  Can also be used directly to update repository or extensions
  If running manually, make sure to activate venv first (if used)
• webui.py:
  Main server script

Any of the above scripts can be used with --help to display detailed usage information and available parameters
For example:

webui.bat --help

Full startup sequence is logged in setup.log, so if you encounter any issues, please check it first

The launcher can perform automatic update of main repository, requirements, extensions and submodules:

• Main repository:
  Update is not performed by default, enable with --upgrade flag
• Requirements:
  Check is performed on each startup and missing requirements are auto-installed, can be skipped with --skip-requirements flag
• Extensions and submodules:
  Update is performed on each startup and installer for each extension is started, can be skipped with --skip-extensions flag
• All checks can be skipped using --quick flag

This repository comes with a large collection of scripts that can be used to process inputs, train, generate, and benchmark models
As well as number of auxiliary scripts that do not rely on WebUI, but can be used for end-to-end solutions such as extract frames from videos, etc.
For full details see Docs

• Scripts are in Scripts
• Everything else is in Wiki
• Except my current TODO