mirror of
https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
199 lines
10 KiB
Markdown
199 lines
10 KiB
Markdown
<div align="center">
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![project logo](docs/assets/invoke_ai_banner.png)
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# InvokeAI: A Stable Diffusion Toolkit
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[![discord badge]][discord link]
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[![latest release badge]][latest release link] [![github stars badge]][github stars link] [![github forks badge]][github forks link]
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[![CI checks on main badge]][CI checks on main link] [![CI checks on dev badge]][CI checks on dev link] [![latest commit to dev badge]][latest commit to dev link]
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[![github open issues badge]][github open issues link] [![github open prs badge]][github open prs link]
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[CI checks on dev badge]: https://flat.badgen.net/github/checks/invoke-ai/InvokeAI/development?label=CI%20status%20on%20dev&cache=900&icon=github
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[CI checks on dev link]: https://github.com/invoke-ai/InvokeAI/actions?query=branch%3Adevelopment
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[CI checks on main badge]: https://flat.badgen.net/github/checks/invoke-ai/InvokeAI/main?label=CI%20status%20on%20main&cache=900&icon=github
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[CI checks on main link]: https://github.com/invoke-ai/InvokeAI/actions/workflows/test-invoke-conda.yml
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[discord badge]: https://flat.badgen.net/discord/members/ZmtBAhwWhy?icon=discord
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[discord link]: https://discord.gg/ZmtBAhwWhy
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[github forks badge]: https://flat.badgen.net/github/forks/invoke-ai/InvokeAI?icon=github
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[github forks link]: https://useful-forks.github.io/?repo=invoke-ai%2FInvokeAI
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[github open issues badge]: https://flat.badgen.net/github/open-issues/invoke-ai/InvokeAI?icon=github
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[github open issues link]: https://github.com/invoke-ai/InvokeAI/issues?q=is%3Aissue+is%3Aopen
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[github open prs badge]: https://flat.badgen.net/github/open-prs/invoke-ai/InvokeAI?icon=github
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[github open prs link]: https://github.com/invoke-ai/InvokeAI/pulls?q=is%3Apr+is%3Aopen
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[github stars badge]: https://flat.badgen.net/github/stars/invoke-ai/InvokeAI?icon=github
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[github stars link]: https://github.com/invoke-ai/InvokeAI/stargazers
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[latest commit to dev badge]: https://flat.badgen.net/github/last-commit/invoke-ai/InvokeAI/development?icon=github&color=yellow&label=last%20dev%20commit&cache=900
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[latest commit to dev link]: https://github.com/invoke-ai/InvokeAI/commits/development
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[latest release badge]: https://flat.badgen.net/github/release/invoke-ai/InvokeAI/development?icon=github
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[latest release link]: https://github.com/invoke-ai/InvokeAI/releases
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</div>
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This is a fork of
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[CompVis/stable-diffusion](https://github.com/CompVis/stable-diffusion),
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the open source text-to-image generator. It provides a streamlined
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process with various new features and options to aid the image
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generation process. It runs on Windows, macOS and Linux machines, with
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GPU cards with as little as 4 GB of RAM. It provides both a polished
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Web interface (see below), and an easy-to-use command-line interface.
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**Quick links**: [[How to Install](#installation)] [<a href="https://discord.gg/ZmtBAhwWhy">Discord Server</a>] [<a href="https://invoke-ai.github.io/InvokeAI/">Documentation and Tutorials</a>] [<a href="https://github.com/invoke-ai/InvokeAI/">Code and Downloads</a>] [<a href="https://github.com/invoke-ai/InvokeAI/issues">Bug Reports</a>] [<a href="https://github.com/invoke-ai/InvokeAI/discussions">Discussion, Ideas & Q&A</a>]
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_Note: InvokeAI is rapidly evolving. Please use the
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[Issues](https://github.com/invoke-ai/InvokeAI/issues) tab to report bugs and make feature
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requests. Be sure to use the provided templates. They will help us diagnose issues faster._
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# Getting Started with InvokeAI
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For full installation and upgrade instructions, please see:
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[InvokeAI Installation Overview](https://invoke-ai.github.io/InvokeAI/installation/)
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1. Go to the bottom of the [Latest Release Page](https://github.com/invoke-ai/InvokeAI/releases/tag/v2.2.3)
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2. Download the .zip file for your OS (Windows/macOS/Linux).
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3. Unzip the file.
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4. If you are on Windows, double-click on the `install.bat` script. On macOS, open a Terminal window, drag the file `install.sh` from Finder into the Terminal, and press return. On Linux, run `install.sh`.
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5. Wait a while, until it is done.
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6. The folder where you ran the installer from will now be filled with lots of files. If you are on Windows, double-click on the `invoke.bat` file. On macOS, open a Terminal window, drag `invoke.sh` from the folder into the Terminal, and press return. On Linux, run `invoke.sh`
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7. 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.
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8. Type `banana sushi` in the box on the top left and click `Invoke`:
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<div align="center"><img src="docs/assets/invoke-web-server-1.png" width=640></div>
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## Table of Contents
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1. [Installation](#installation)
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2. [Hardware Requirements](#hardware-requirements)
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3. [Features](#features)
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4. [Latest Changes](#latest-changes)
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5. [Troubleshooting](#troubleshooting)
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6. [Contributing](#contributing)
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7. [Contributors](#contributors)
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8. [Support](#support)
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9. [Further Reading](#further-reading)
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### Installation
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This fork is supported across Linux, Windows and Macintosh. Linux
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users can use either an Nvidia-based card (with CUDA support) or an
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AMD card (using the ROCm driver). For full installation and upgrade
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instructions, please see:
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[InvokeAI Installation Overview](https://invoke-ai.github.io/InvokeAI/installation/INSTALL_SOURCE/)
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### Hardware Requirements
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InvokeAI is supported across Linux, Windows and macOS. Linux
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users can use either an Nvidia-based card (with CUDA support) or an
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AMD card (using the ROCm driver).
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#### System
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You wil need one of the following:
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- An NVIDIA-based graphics card with 4 GB or more VRAM memory.
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- An Apple computer with an M1 chip.
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We do not recommend the GTX 1650 or 1660 series video cards. They are
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unable to run in half-precision mode and do not have sufficient VRAM
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to render 512x512 images.
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#### Memory
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- At least 12 GB Main Memory RAM.
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#### Disk
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- At least 12 GB of free disk space for the machine learning model, Python, and all its dependencies.
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**Note**
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If you have a Nvidia 10xx series card (e.g. the 1080ti), please
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run the dream script in full-precision mode as shown below.
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Similarly, specify full-precision mode on Apple M1 hardware.
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Precision is auto configured based on the device. If however you encounter
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errors like 'expected type Float but found Half' or 'not implemented for Half'
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you can try starting `invoke.py` with the `--precision=float32` flag to your initialization command
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```bash
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(invokeai) ~/InvokeAI$ python scripts/invoke.py --precision=float32
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```
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Or by updating your InvokeAI configuration file with this argument.
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### Features
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#### Major Features
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- [Web Server](https://invoke-ai.github.io/InvokeAI/features/WEB/)
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- [Interactive Command Line Interface](https://invoke-ai.github.io/InvokeAI/features/CLI/)
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- [Image To Image](https://invoke-ai.github.io/InvokeAI/features/IMG2IMG/)
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- [Inpainting Support](https://invoke-ai.github.io/InvokeAI/features/INPAINTING/)
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- [Outpainting Support](https://invoke-ai.github.io/InvokeAI/features/OUTPAINTING/)
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- [Upscaling, face-restoration and outpainting](https://invoke-ai.github.io/InvokeAI/features/POSTPROCESS/)
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- [Reading Prompts From File](https://invoke-ai.github.io/InvokeAI/features/PROMPTS/#reading-prompts-from-a-file)
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- [Prompt Blending](https://invoke-ai.github.io/InvokeAI/features/PROMPTS/#prompt-blending)
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- [Thresholding and Perlin Noise Initialization Options](https://invoke-ai.github.io/InvokeAI/features/OTHER/#thresholding-and-perlin-noise-initialization-options)
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- [Negative/Unconditioned Prompts](https://invoke-ai.github.io/InvokeAI/features/PROMPTS/#negative-and-unconditioned-prompts)
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- [Variations](https://invoke-ai.github.io/InvokeAI/features/VARIATIONS/)
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- [Personalizing Text-to-Image Generation](https://invoke-ai.github.io/InvokeAI/features/TEXTUAL_INVERSION/)
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- [Simplified API for text to image generation](https://invoke-ai.github.io/InvokeAI/features/OTHER/#simplified-api)
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#### Other Features
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- [Google Colab](https://invoke-ai.github.io/InvokeAI/features/OTHER/#google-colab)
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- [Seamless Tiling](https://invoke-ai.github.io/InvokeAI/features/OTHER/#seamless-tiling)
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- [Shortcut: Reusing Seeds](https://invoke-ai.github.io/InvokeAI/features/OTHER/#shortcuts-reusing-seeds)
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- [Preload Models](https://invoke-ai.github.io/InvokeAI/features/OTHER/#preload-models)
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### Latest Changes
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For our latest changes, view our [Release Notes](https://github.com/invoke-ai/InvokeAI/releases)
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### Troubleshooting
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Please check out our **[Q&A](https://invoke-ai.github.io/InvokeAI/help/TROUBLESHOOT/#faq)** to get solutions for common installation
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problems and other issues.
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# Contributing
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Anyone who wishes to contribute to this project, whether documentation, features, bug fixes, code
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cleanup, testing, or code reviews, is very much encouraged to do so.
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To join, just raise your hand on the InvokeAI Discord server (#dev-chat) or the GitHub discussion board.
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If you are unfamiliar with how
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to contribute to GitHub projects, here is a
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[Getting Started Guide](https://opensource.com/article/19/7/create-pull-request-github). A full set of contribution guidelines, along with templates, are in progress, but for now the most
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important thing is to **make your pull request against the "development" branch**, and not against
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"main". This will help keep public breakage to a minimum and will allow you to propose more radical
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changes.
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We hope you enjoy using our software as much as we enjoy creating it,
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and we hope that some of those of you who are reading this will elect
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to become part of our community.
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Welcome to InvokeAI!
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### Contributors
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This fork is a combined effort of various people from across the world.
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[Check out the list of all these amazing people](https://invoke-ai.github.io/InvokeAI/other/CONTRIBUTORS/). We thank them for
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their time, hard work and effort.
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### Support
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For support, please use this repository's GitHub Issues tracking service. Feel free to send me an
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email if you use and like the script.
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Original portions of the software are Copyright (c) 2020
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[Lincoln D. Stein](https://github.com/lstein)
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### Further Reading
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Please see the original README for more information on this software and underlying algorithm,
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located in the file [README-CompViz.md](https://invoke-ai.github.io/InvokeAI/other/README-CompViz/).
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