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Changelog#

v2.3.0 (15 January 2023)#

**Transition to diffusers

Version 2.3 provides support for both the traditional .ckpt weight checkpoint files as well as the HuggingFace diffusers format. This introduces several changes you should know about.

  1. The models.yaml format has been updated. There are now two different type of configuration stanza. The traditional ckpt one will look like this, with a format of ckpt and a weights field that points to the absolute or ROOTDIR-relative location of the ckpt file.
inpainting-1.5:
   description: RunwayML SD 1.5 model optimized for inpainting (4.27 GB)
   repo_id: runwayml/stable-diffusion-inpainting
   format: ckpt
   width: 512
   height: 512
   weights: models/ldm/stable-diffusion-v1/sd-v1-5-inpainting.ckpt
   config: configs/stable-diffusion/v1-inpainting-inference.yaml
   vae: models/ldm/stable-diffusion-v1/vae-ft-mse-840000-ema-pruned.ckpt

A configuration stanza for a diffusers model hosted at HuggingFace will look like this, with a format of diffusers and a repo_id that points to the repository ID of the model on HuggingFace:

stable-diffusion-2.1:
description: Stable Diffusion version 2.1 diffusers model (5.21 GB)
repo_id: stabilityai/stable-diffusion-2-1
format: diffusers

A configuration stanza for a diffuers model stored locally should look like this, with a format of diffusers, but a path field that points at the directory that contains model_index.json:

waifu-diffusion:
description: Latest waifu diffusion 1.4
format: diffusers
path: models/diffusers/hakurei-haifu-diffusion-1.4
  1. In order of precedence, InvokeAI will now use HF_HOME, then XDG_CACHE_HOME, then finally default to ROOTDIR/models to store HuggingFace diffusers models.

Consequently, the format of the models directory has changed to mimic the HuggingFace cache directory. When HF_HOME and XDG_HOME are not set, diffusers models are now automatically downloaded and retrieved from the directory ROOTDIR/models/diffusers, while other models are stored in the directory ROOTDIR/models/hub. This organization is the same as that used by HuggingFace for its cache management.

This allows you to share diffusers and ckpt model files easily with other machine learning applications that use the HuggingFace libraries. To do this, set the environment variable HF_HOME before starting up InvokeAI to tell it what directory to cache models in. To tell InvokeAI to use the standard HuggingFace cache directory, you would set HF_HOME like this (Linux/Mac):

export HF_HOME=~/.cache/huggingface

Both HuggingFace and InvokeAI will fall back to the XDG_CACHE_HOME environment variable if HF_HOME is not set; this path takes precedence over ROOTDIR/models to allow for the same sharing with other machine learning applications that use HuggingFace libraries.

  1. If you upgrade to InvokeAI 2.3.* from an earlier version, there will be a one-time migration from the old models directory format to the new one. You will see a message about this the first time you start invoke.py.

  2. Both the front end back ends of the model manager have been rewritten to accommodate diffusers. You can import models using their local file path, using their URLs, or their HuggingFace repo_ids. On the command line, all these syntaxes work:

!import_model stabilityai/stable-diffusion-2-1-base
!import_model /opt/sd-models/sd-1.4.ckpt
!import_model https://huggingface.co/Fictiverse/Stable_Diffusion_PaperCut_Model/blob/main/PaperCut_v1.ckpt

**KNOWN BUGS (15 January 2023)

  1. On CUDA systems, the 768 pixel stable-diffusion-2.0 and stable-diffusion-2.1 models can only be run as diffusers models when the xformer library is installed and configured. Without xformers, InvokeAI returns black images.

  2. Inpainting and outpainting have regressed in quality.

Both these issues are being actively worked on.

v2.2.4 (11 December 2022)#

the invokeai directory

Previously there were two directories to worry about, the directory that contained the InvokeAI source code and the launcher scripts, and the invokeai directory that contained the models files, embeddings, configuration and outputs. With the 2.2.4 release, this dual system is done away with, and everything, including the invoke.bat and invoke.sh launcher scripts, now live in a directory named invokeai. By default this directory is located in your home directory (e.g. \Users\yourname on Windows), but you can select where it goes at install time.

After installation, you can delete the install directory (the one that the zip file creates when it unpacks). Do not delete or move the invokeai directory!

Initialization file invokeai/invokeai.init

You can place frequently-used startup options in this file, such as the default number of steps or your preferred sampler. To keep everything in one place, this file has now been moved into the invokeai directory and is named invokeai.init.

To update from Version 2.2.3

The easiest route is to download and unpack one of the 2.2.4 installer files. When it asks you for the location of the invokeai runtime directory, respond with the path to the directory that contains your 2.2.3 invokeai. That is, if invokeai lives at C:\Users\fred\invokeai, then answer with C:\Users\fred and answer "Y" when asked if you want to reuse the directory.

The update.sh (update.bat) script that came with the 2.2.3 source installer does not know about the new directory layout and won't be fully functional.

To update to 2.2.5 (and beyond) there's now an update path

As they become available, you can update to more recent versions of InvokeAI using an update.sh (update.bat) script located in the invokeai directory. Running it without any arguments will install the most recent version of InvokeAI. Alternatively, you can get set releases by running the update.sh script with an argument in the command shell. This syntax accepts the path to the desired release's zip file, which you can find by clicking on the green "Code" button on this repository's home page.

Other 2.2.4 Improvements

v2.2.3 (2 December 2022)#

Note

This point release removes references to the binary installer from the installation guide. The binary installer is not stable at the current time. First time users are encouraged to use the "source" installer as described in Installing InvokeAI with the Source Installer

With InvokeAI 2.2, this project now provides enthusiasts and professionals a robust workflow solution for creating AI-generated and human facilitated compositions. Additional enhancements have been made as well, improving safety, ease of use, and installation.

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).

You can see the release video here, which introduces the main WebUI enhancement for version 2.2 - The Unified Canvas. This new workflow is the biggest enhancement added to the WebUI to date, and unlocks a stunning amount of potential for users to create and iterate on their creations. The following sections describe what's new for InvokeAI.

v2.2.2 (30 November 2022)#

Note

The binary installer is not ready for prime time. First time users are recommended to install via the "source" installer accessible through the links at the bottom of this page.****

With InvokeAI 2.2, this project now provides enthusiasts and professionals a robust workflow solution for creating AI-generated and human facilitated compositions. Additional enhancements have been made as well, improving safety, ease of use, and installation.

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).

You can see the release video here, which introduces the main WebUI enhancement for version 2.2 - The Unified Canvas. This new workflow is the biggest enhancement added to the WebUI to date, and unlocks a stunning amount of potential for users to create and iterate on their creations. The following sections describe what's new for InvokeAI.

v2.2.0 (2 December 2022)#

With InvokeAI 2.2, this project now provides enthusiasts and professionals a robust workflow solution for creating AI-generated and human facilitated compositions. Additional enhancements have been made as well, improving safety, ease of use, and installation.

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).

You can see the release video here, which introduces the main WebUI enhancement for version 2.2 - The Unified Canvas. This new workflow is the biggest enhancement added to the WebUI to date, and unlocks a stunning amount of potential for users to create and iterate on their creations. The following sections describe what's new for InvokeAI.

v2.1.3 (13 November 2022)#

  • A choice of installer scripts that automate installation and configuration. See Installation.
  • A streamlined manual installation process that works for both Conda and PIP-only installs. See Manual Installation.
  • The ability to save frequently-used startup options (model to load, steps, sampler, etc) in a .invokeai file. See Client
  • Support for AMD GPU cards (non-CUDA) on Linux machines.
  • Multiple bugs and edge cases squashed.

v2.1.0 (2 November 2022)#

v2.0.1 (13 October 2022)#

  • fix noisy images at high step count when using k* samplers
  • dream.py script now calls invoke.py module directly rather than via a new python process (which could break the environment)

v2.0.0 (9 October 2022)#

  • dream.py script renamed invoke.py. A dream.py script wrapper remains for backward compatibility.
  • Completely new WebGUI - launch with python3 scripts/invoke.py --web
  • Support for inpainting and outpainting
  • img2img runs on all k* samplers
  • Support for negative prompts
  • Support for CodeFormer face reconstruction
  • Support for Textual Inversion on Macintoshes
  • Support in both WebGUI and CLI for post-processing of previously-generated images using facial reconstruction, ESRGAN upscaling, outcropping (similar to DALL-E infinite canvas), and "embiggen" upscaling. See the !fix command.
  • New --hires option on invoke> line allows larger images to be created without duplicating elements, at the cost of some performance.
  • New --perlin and --threshold options allow you to add and control variation during image generation (see Thresholding and Perlin Noise Initialization)
  • Extensive metadata now written into PNG files, allowing reliable regeneration of images and tweaking of previous settings.
  • Command-line completion in invoke.py now works on Windows, Linux and Mac platforms.
  • Improved command-line completion behavior New commands added:
  • List command-line history with !history
  • Search command-line history with !search
  • Clear history with !clear
  • Deprecated --full_precision / -F. Simply omit it and invoke.py will auto configure. To switch away from auto use the new flag like --precision=float32.

v1.14 (11 September 2022)#

  • 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.

v1.13 (3 September 2022)#

  • Support image variations (see VARIATIONS (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 invoke.py command line as the default.
  • Miscellaneous internal bug and stability fixes.
  • Works on M1 Apple hardware.
  • Multiple bug fixes.

v1.12 (28 August 2022)#

  • Improved file handling, including ability to read prompts from standard input. (kudos to Yunsaki
  • The web server is now integrated with the invoke.py script. Invoke by adding --web to the invoke.py command arguments.
  • Face restoration and upscaling via GFPGAN and Real-ESGAN are now automatically enabled if the GFPGAN directory is located as a sibling to Stable Diffusion. VRAM requirements are modestly reduced. Thanks to both Blessedcoolant and Oceanswave for their work on this.
  • You can now swap samplers on the invoke> command line. Blessedcoolant

v1.11 (26 August 2022)#

  • NEW FEATURE: Support upscaling and face enhancement using the GFPGAN module. (kudos to Oceanswave
  • You now can specify a seed of -1 to use the previous image's seed, -2 to use the seed for the image generated before that, etc. Seed memory only extends back to the previous command, but will work on all images generated with the -n# switch.
  • Variant generation support temporarily disabled pending more general solution.
  • Created a feature branch named yunsaki-morphing-invoke which adds experimental support for iteratively modifying the prompt and its parameters. Please seePull Request #86 for a synopsis of how this works. Note that when this feature is eventually added to the main branch, it will may be modified significantly.

v1.10 (25 August 2022)#

  • A barebones but fully functional interactive web server for online generation of txt2img and img2img.

v1.09 (24 August 2022)#

v1.08 (24 August 2022)#

  • Escape single quotes on the invoke> command before trying to parse. This avoids parse errors.
  • Removed instruction to get Python3.8 as first step in Windows install. Anaconda3 does it for you.
  • Added bounds checks for numeric arguments that could cause crashes.
  • Cleaned up the copyright and license agreement files.

v1.07 (23 August 2022)#

  • Image filenames will now never fill gaps in the sequence, but will be assigned the next higher name in the chosen directory. This ensures that the alphabetic and chronological sort orders are the same.

v1.06 (23 August 2022)#

  • Added weighted prompt support contributed by xraxra
  • Example of using weighted prompts to tweak a demonic figure contributed by bmaltais

v1.05 (22 August 2022 - after the drop)#

  • Filenames now use the following formats: 000010.95183149.png -- Two files produced by the same command (e.g. -n2), 000010.26742632.png -- distinguished by a different seed.

000011.455191342.01.png -- Two files produced by the same command using 000011.455191342.02.png -- a batch size>1 (e.g. -b2). They have the same seed.

000011.4160627868.grid#1-4.png -- a grid of four images (-g); the whole grid can be regenerated with the indicated key

  • It should no longer be possible for one image to overwrite another
  • You can use the "cd" and "pwd" commands at the invoke> prompt to set and retrieve the path of the output directory.

v1.04 (22 August 2022 - after the drop)#

  • Updated README to reflect installation of the released weights.
  • Suppressed very noisy and inconsequential warning when loading the frozen CLIP tokenizer.

v1.03 (22 August 2022)#

  • The original txt2img and img2img scripts from the CompViz repository have been moved into a subfolder named "orig_scripts", to reduce confusion.

v1.02 (21 August 2022)#

  • A copy of the prompt and all of its switches and options is now stored in the corresponding image in a tEXt metadata field named "Dream". You can read the prompt using scripts/images2prompt.py, or an image editor that allows you to explore the full metadata. Please run "conda env update" to load the k_lms dependencies!!

v1.01 (21 August 2022)#

  • added k_lms sampling. Please run "conda env update" to load the k_lms dependencies!!
  • use half precision arithmetic by default, resulting in faster execution and lower memory requirements Pass argument --full_precision to invoke.py to get slower but more accurate image generation
Last update: February 8, 2023
Created: August 30, 2022