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Releases

InvokeAI Version 2.1 - A Stable Diffusion Toolkit

The invoke-ai team is excited to be able to share the release of InvokeAI 2.1 - A Stable Diffusion Toolkit, a project that aims to provide enthusiasts and professionals both a suite of robust image creation tools. Optimized for efficiency, InvokeAI needs only ~3.5GB of VRAM to generate a 512x768 image (and less for smaller images), and is compatible with Windows/Linux/Mac (M1 & M2).

InvokeAI was one of the earliest forks of the core CompVis repo (formerly lstein/stable-diffusion), and recently evolved into a full-fledged community driven and open source stable diffusion toolkit. Version 2.1 of the tool introduces multiple new features and performance enhancements.

This 14-minute YouTube video introduces you to some of the new features contained in this release. The following sections describe what’s new in the Web interface (WebGUI) and the command-line interface (CLI).

Major new features

  • Inpainting support in the WebGUI
  • Greatly improved navigation and user experience in the WebGUI
  • The prompt syntax has been enhanced with prompt weighting, cross-attention and prompt merging.
  • You can now load multiple models and switch among them quickly without leaving the CLI or WebGUI.
  • The installation process (via scripts/preload_models.py) now lets you select among several popular Stable Diffusion models and downloads and installs them on your behalf. Among other models, this script will install the current Stable Diffusion 1.5 model as well as a StabilityAI variable autoencoder (VAE) which improves face generation.
  • Tired of struggling with photoeditors to get the masked region of for inpainting just right? Let the AI make the mask for you using text masking. This feature allows you to specify the part of the image to paint over using just English-language phrases.
  • Tired of seeing the head of your subjects cropped off? Uncrop them in the CLI with the outcrop feature.
  • Tired of seeing your subject’s bodies duplicated or mangled when generating larger-dimension images? Check out the --hires option in the CLI, or select the corresponding toggle in the WebGUI.
  • We now support textual inversion and fine-tune .bin styles and subjects from the Hugging Face archive of SD Concepts. Load the .bin file using the --embedding_path option. (The next version will support merging and loading of multiple simultaneous models).

Installation

To install InvokeAI from scratch, please see the Installation section of the InvokeAI docs.

Upgrading

For those wishing to upgrade from an earlier version, please use the following recipe from within the InvokeAI directory:

Mac users:

conda deactivate
git checkout main
git pull
rm -rf src
conda update -f environment-mac.yml
conda activate invokeai
python scripts/preload_models.py

Windows users:

conda deactivate
git checkout main
git pull
rmdir src /s
conda update
conda activate invokeai
python scripts\preload_models.py

Linux Users

conda deactivate
git checkout main
git pull
rm -rf src
conda update
conda activate invokeai
python scripts/preload_models.py

Contributing

Please see CONTRIBUTORS for a list of the many individuals who contributed to this project. Also many thanks to the dozens of patient testers who flushed out bugs in this release before it went live.

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. If you are unfamiliar with how to contribute to GitHub projects, here is a Getting Started Guide.

The most important thing is to know about contributing code is to make your pull request against the “development” branch, and not against “main”. This will help keep public breakage to a minimum and will allow you to propose more radical changes.

Support

For support, please use this repository’s GitHub Issues tracking service. Live support is also available on the InvokeAI Discord server.

Full change log since 2.0.2

New Contributors

Full Changelog: https://github.com/invoke-ai/InvokeAI/compare/v2.0.1…2.1.0-rc1

InvokeAI Version 2.0.2 - A Stable Diffusion Toolkit

The invoke-ai team is excited to be able to share the release of InvokeAI 2.0 - A Stable Diffusion Toolkit, a project that aims to provide enthusiasts and professionals both a suite of robust image creation tools. Optimized for efficiency, InvokeAI needs only ~3.5GB of VRAM to generate a 512x768 image (and less for smaller images), and is compatible with Windows/Linux/Mac (M1 & M2).

InvokeAI was one of the earliest forks of the core CompVis repo (formerly lstein/stable-diffusion), and recently evolved into a full-fledged community driven and open source stable diffusion toolkit named InvokeAI. Version 2.0.0 of the tool introduces an entirely new WebUI Front-end with a Desktop mode, and an optimized back-end server that can be interacted with via CLI or extended with your own fork.

Release 2.0.2 updates three Python dependencies that were recently reported to have critical security holes, and enhances documentation. Otherwise, the feature set is identical to 2.0.1.

This version of the app improves in-app workflows leveraging GFPGAN and Codeformer for face restoration, and RealESRGAN upscaling - Additionally, the CLI also supports a large variety of features:

  • Inpainting
  • Outpainting
  • Negative Prompts (prompt unconditioning)
  • Fast online model switching
  • Textual Inversion
  • Improved Quality for Hi-Resolution Images (Embiggen, Hi-res Fixes, etc.)
  • And more…

Future updates planned included UI driven outpainting/inpainting, robust Cross Attention support, and an advanced node workflow for automating and sharing your workflows with the community.

What’s Changed

New Contributors

Full Changelog: https://github.com/invoke-ai/InvokeAI/compare/v2.0.0…v2.0.1

What’s Changed

New Contributors

Full Changelog: https://github.com/invoke-ai/InvokeAI/compare/v2.0.1…v2.0.2

InvokeAI Version 2.0.1 - A Stable Diffusion Toolkit

The invoke-ai team is excited to be able to share the release of InvokeAI 2.0 - A Stable Diffusion Toolkit, a project that aims to provide enthusiasts and professionals both a suite of robust image creation tools. Optimized for efficiency, InvokeAI needs only ~3.5GB of VRAM to generate a 512x768 image (and less for smaller images), and is compatible with Windows/Linux/Mac (M1 & M2).

InvokeAI was one of the earliest forks of the core CompVis repo (formerly lstein/stable-diffusion), and recently evolved into a full-fledged community driven and open source stable diffusion toolkit named InvokeAI. Version 2.0.0 of the tool introduces an entirely new WebUI Front-end with a Desktop mode, and an optimized back-end server that can be interacted with via CLI or extended with your own fork.

Release 2.0.1 corrects an error that was causing the k* samplers to produce noisy images at high step counts. Otherwise the feature set is the same as 2.0.0.

This version of the app improves in-app workflows leveraging GFPGAN and Codeformer for face restoration, and RealESRGAN upscaling - Additionally, the CLI also supports a large variety of features:

  • Inpainting
  • Outpainting
  • Negative Prompts (prompt unconditioning)
  • Fast online model switching
  • Textual Inversion
  • Improved Quality for Hi-Resolution Images (Embiggen, Hi-res Fixes, etc.)
  • And more…

Future updates planned included UI driven outpainting/inpainting, robust Cross Attention support, and an advanced node workflow for automating and sharing your workflows with the community.

What’s Changed

New Contributors

Full Changelog: https://github.com/invoke-ai/InvokeAI/compare/v2.0.0…v2.0.1

InvokeAI Version 2.0.0 - A Stable Diffusion Toolkit

The invoke-ai team is excited to be able to share the release of InvokeAI 2.0 - A Stable Diffusion Toolkit, a project that aims to provide enthusiasts and professionals both a suite of robust image creation tools. Optimized for efficiency, InvokeAI needs only ~3.5GB of VRAM to generate a 512x768 image (and less for smaller images), and is compatible with Windows/Linux/Mac (M1 & M2).

InvokeAI was one of the earliest forks of the core CompVis repo (formerly lstein/stable-diffusion), and recently evolved into a full-fledged community driven and open source stable diffusion toolkit named InvokeAI. Version 2.0.0 of the tool introduces an entirely new WebUI Front-end with a Desktop mode, and an optimized back-end server that can be interacted with via CLI or extended with your own fork.

This version of the app improves in-app workflows leveraging GFPGAN and Codeformer for face restoration, and RealESRGAN upscaling - Additionally, the CLI also supports a large variety of features:

  • Inpainting
  • Outpainting
  • Negative Prompts (prompt unconditioning)
  • Textual Inversion
  • Improved Quality for Hi-Resolution Images (Embiggen, Hi-res Fixes, etc.)
  • And more…

Future updates planned included UI driven outpainting/inpainting, robust Cross Attention support, and an advanced node workflow for automating and sharing your workflows with the community.

SD-Dream Version 1.14.1

This is identical to release 1.14 except that it reverts the name of the conda environment from “sd-ldm” back to the original “ldm”.

Features from 1.14:

  • Memory optimizations for small-RAM cards. 512x512 now possible on 4 GB GPUs.
  • Full support for Apple hardware with M1 or M2 chips.
  • Add “seamless mode” for circular tiling of image. Generates beautiful effects. (prixt).
  • Inpainting support.
  • Improved web server GUI.
  • Lots of code and documentation cleanups.

SD-Dream Version 1.14

  • Memory optimizations for small-RAM cards. 512x512 now possible on 4 GB GPUs.
  • Full support for Apple hardware with M1 or M2 chips.
  • Add “seamless mode” for circular tiling of image. Generates beautiful effects. (prixt).
  • Inpainting support.
  • Improved web server GUI.
  • Lots of code and documentation cleanups.

SD-Dream Version 1.13

New features and bug fixes:

  • Support image variations (see VARIATIONS.md) (Kevin Gibbons and many contributors and reviewers)
  • Supports a Google Colab notebook for a standalone server running on Google hardware Arturo Mendivil
  • WebUI supports GFPGAN/ESRGAN facial reconstruction and upscaling Kevin Gibbons
  • WebUI supports incremental display of in-progress images during generation Kevin Gibbons
  • A new configuration file scheme that allows new models (including upcoming stable-diffusion-v1.5) to be added without altering the code. (David Wager)
  • Can specify —grid on dream.py command line as the default.
  • Miscellaneous internal bug and stability fixes.
  • Works on M1 Apple hardware (several contributors, but particular thanks to James Reynolds )
  • Multiple bug fixes.
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