b913e1e11e
A long-standing issue with importing legacy checkpoints (both ckpt and
safetensors) is that the user has to identify the correct config file,
either by providing its path or by selecting which type of model the
checkpoint is (e.g. "v1 inpainting"). In addition, some users wish to
provide custom VAEs for use with the model. Currently this is done in
the WebUI by importing the model, editing it, and then typing in the
path to the VAE.
## Model configuration file selection
To improve the user experience, the model manager's `heuristic_import()`
method has been enhanced as follows:
1. When initially called, the caller can pass a config file path, in
which case it will be used.
2. If no config file provided, the method looks for a .yaml file in the
same directory as the model which bears the same basename. e.g.
```
my-new-model.safetensors
my-new-model.yaml
```
The yaml file is then used as the configuration file for importation and
conversion.
3. If no such file is found, then the method opens up the checkpoint and
probes it to determine whether it is V1, V1-inpaint or V2. If it is a V1
format, then the appropriate v1-inference.yaml config file is used.
Unfortunately there are two V2 variants that cannot be distinguished by
introspection.
4. If the probe algorithm is unable to determine the model type, then
its last-ditch effort is to execute an optional callback function that
can be provided by the caller. This callback, named
`config_file_callback` receives the path to the legacy checkpoint and
returns the path to the config file to use. The CLI uses to put up a
multiple choice prompt to the user. The WebUI **could** use this to
prompt the user to choose from a radio-button selection.
5. If the config file cannot be determined, then the import is
abandoned.
## Custom VAE Selection
The user can attach a custom VAE to the imported and converted model by
copying the desired VAE into the same directory as the file to be
imported, and giving it the same basename. E.g.:
```
my-new-model.safetensors
my-new-model.vae.pt
```
For this to work, the VAE must end with ".vae.pt", ".vae.ckpt", or
".vae.safetensors". The indicated VAE will be converted into diffusers
format and stored with the converted models file, so the ".pt" file can
be deleted after conversion.
No facility is currently provided to swap a diffusers VAE at import
time, but this can be done after the fact using the WebUI and CLI's
model editing functions.
Note that this is the same fix that was applied to the 2.3 branch in
#3043 . This applies to `main`.
|
||
|---|---|---|
| .dev_scripts | ||
| .github | ||
| binary_installer | ||
| coverage | ||
| docker | ||
| docs | ||
| installer | ||
| invokeai | ||
| notebooks | ||
| scripts | ||
| static | ||
| tests | ||
| .dockerignore | ||
| .editorconfig | ||
| .git-blame-ignore-revs | ||
| .gitattributes | ||
| .gitignore | ||
| .gitmodules | ||
| .prettierrc.yaml | ||
| CODE_OF_CONDUCT.md | ||
| InvokeAI_Statement_of_Values.md | ||
| LICENSE | ||
| LICENSE-ModelWeights.txt | ||
| mkdocs.yml | ||
| pyproject.toml | ||
| README.md | ||
| shell.nix | ||
| Stable_Diffusion_v1_Model_Card.md | ||
InvokeAI: A Stable Diffusion Toolkit
InvokeAI is a leading creative engine built to empower professionals and enthusiasts alike. Generate and create stunning visual media using the latest AI-driven technologies. InvokeAI offers an industry leading Web Interface, interactive Command Line Interface, and also serves as the foundation for multiple commercial products.
Quick links: [How to Install] [Discord Server] [Documentation and Tutorials] [Code and Downloads] [Bug Reports] [Discussion, Ideas & Q&A]
Note: InvokeAI is rapidly evolving. Please use the Issues tab to report bugs and make feature requests. Be sure to use the provided templates. They will help us diagnose issues faster.
Table of Contents
- Quick Start
- Installation
- Hardware Requirements
- Features
- Latest Changes
- Troubleshooting
- Contributing
- Contributors
- Support
- Further Reading
Getting Started with InvokeAI
For full installation and upgrade instructions, please see: InvokeAI Installation Overview
Automatic Installer (suggested for 1st time users)
-
Go to the bottom of the Latest Release Page
-
Download the .zip file for your OS (Windows/macOS/Linux).
-
Unzip the file.
-
If you are on Windows, double-click on the
install.batscript. On macOS, open a Terminal window, drag the fileinstall.shfrom Finder into the Terminal, and press return. On Linux, runinstall.sh. -
You'll be asked to confirm the location of the folder in which to install InvokeAI and its image generation model files. Pick a location with at least 15 GB of free memory. More if you plan on installing lots of models.
-
Wait while the installer does its thing. After installing the software, the installer will launch a script that lets you configure InvokeAI and select a set of starting image generaiton models.
-
Find the folder that InvokeAI was installed into (it is not the same as the unpacked zip file directory!) The default location of this folder (if you didn't change it in step 5) is
~/invokeaion Linux/Mac systems, andC:\Users\YourName\invokeaion Windows. This directory will contain launcher scripts namedinvoke.shandinvoke.bat. -
On Windows systems, double-click on the
invoke.batfile. On macOS, open a Terminal window, draginvoke.shfrom the folder into the Terminal, and press return. On Linux, runinvoke.sh -
Press 2 to open the "browser-based UI", press enter/return, wait a minute or two for Stable Diffusion to start up, then open your browser and go to http://localhost:9090.
-
Type
banana sushiin the box on the top left and clickInvoke
Command-Line Installation (for users familiar with Terminals)
You must have Python 3.9 or 3.10 installed on your machine. Earlier or later versions are not supported.
-
Open a command-line window on your machine. The PowerShell is recommended for Windows.
-
Create a directory to install InvokeAI into. You'll need at least 15 GB of free space:
mkdir invokeai -
Create a virtual environment named
.venvinside this directory and activate it:cd invokeai python -m venv .venv --prompt InvokeAI -
Activate the virtual environment (do it every time you run InvokeAI)
For Linux/Mac users:
source .venv/bin/activateFor Windows users:
.venv\Scripts\activate -
Install the InvokeAI module and its dependencies. Choose the command suited for your platform & GPU.
For Windows/Linux with an NVIDIA GPU:
pip install "InvokeAI[xformers]" --use-pep517 --extra-index-url https://download.pytorch.org/whl/cu117For Linux with an AMD GPU:
pip install InvokeAI --use-pep517 --extra-index-url https://download.pytorch.org/whl/rocm5.4.2For Macintoshes, either Intel or M1/M2:
pip install InvokeAI --use-pep517 -
Configure InvokeAI and install a starting set of image generation models (you only need to do this once):
invokeai-configure -
Launch the web server (do it every time you run InvokeAI):
invokeai --web -
Point your browser to http://localhost:9090 to bring up the web interface.
-
Type
banana sushiin the box on the top left and clickInvoke.
Be sure to activate the virtual environment each time before re-launching InvokeAI,
using source .venv/bin/activate or .venv\Scripts\activate.
Detailed Installation Instructions
This fork is supported across Linux, Windows and Macintosh. Linux users can use either an Nvidia-based card (with CUDA support) or an AMD card (using the ROCm driver). For full installation and upgrade instructions, please see: InvokeAI Installation Overview
Hardware Requirements
InvokeAI is supported across Linux, Windows and macOS. Linux users can use either an Nvidia-based card (with CUDA support) or an AMD card (using the ROCm driver).
System
You will need one of the following:
- An NVIDIA-based graphics card with 4 GB or more VRAM memory.
- An Apple computer with an M1 chip.
- An AMD-based graphics card with 4GB or more VRAM memory. (Linux only)
We do not recommend the GTX 1650 or 1660 series video cards. They are unable to run in half-precision mode and do not have sufficient VRAM to render 512x512 images.
Memory
- At least 12 GB Main Memory RAM.
Disk
- At least 12 GB of free disk space for the machine learning model, Python, and all its dependencies.
Features
Feature documentation can be reviewed by navigating to the InvokeAI Documentation page
Web Server & UI
InvokeAI offers a locally hosted Web Server & React Frontend, with an industry leading user experience. The Web-based UI allows for simple and intuitive workflows, and is responsive for use on mobile devices and tablets accessing the web server.
Unified Canvas
The Unified Canvas is a fully integrated canvas implementation with support for all core generation capabilities, in/outpainting, brush tools, and more. This creative tool unlocks the capability for artists to create with AI as a creative collaborator, and can be used to augment AI-generated imagery, sketches, photography, renders, and more.
Advanced Prompt Syntax
InvokeAI's advanced prompt syntax allows for token weighting, cross-attention control, and prompt blending, allowing for fine-tuned tweaking of your invocations and exploration of the latent space.
Command Line Interface
For users utilizing a terminal-based environment, or who want to take advantage of CLI features, InvokeAI offers an extensive and actively supported command-line interface that provides the full suite of generation functionality available in the tool.
Other features
- Support for both ckpt and diffusers models
- SD 2.0, 2.1 support
- Noise Control & Tresholding
- Popular Sampler Support
- Upscaling & Face Restoration Tools
- Embedding Manager & Support
- Model Manager & Support
Coming Soon
- Node-Based Architecture & UI
- And more...
Latest Changes
For our latest changes, view our Release Notes and the CHANGELOG.
Troubleshooting
Please check out our Q&A to get solutions for common installation problems and other issues.
Contributing
Anyone who wishes to contribute to this project, whether documentation, features, bug fixes, code cleanup, testing, or code reviews, is very much encouraged to do so.
To join, just raise your hand on the InvokeAI Discord server (#dev-chat) or the GitHub discussion board.
If you'd like to help with translation, please see our translation guide.
If you are unfamiliar with how to contribute to GitHub projects, here is a Getting Started Guide. A full set of contribution guidelines, along with templates, are in progress. You can make your pull request against the "main" branch.
We hope you enjoy using our software as much as we enjoy creating it, and we hope that some of those of you who are reading this will elect to become part of our community.
Welcome to InvokeAI!
Contributors
This fork is a combined effort of various people from across the world. Check out the list of all these amazing people. We thank them for their time, hard work and effort.
Thanks to Weblate for generously providing translation services to this project.
Support
For support, please use this repository's GitHub Issues tracking service, or join the Discord.
Original portions of the software are Copyright (c) 2023 by respective contributors.