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v4.2.7rc1

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@psychedelicious psychedelicious released this 24 Jul 23:15
· 2728 commits to main since this release
v4.2.7rc1
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v4.2.7rc1 includes gallery improvements and some major features focused on upscaling.

Upscaling

We've added a dedicated upscaling tab, support for custom upscaling models, and some new nodes.

Thanks to @RyanJDick (backend implementation), @chainchompa (frontend) and @maryhipp (frontend) for working on this!

Dedicated Upscaling Tab

The new upscaling tab provides a simple and powerful UI to Invoke's MultiDiffusion implementation. This builds on the workflow released in v4.2.6, allowing for memory-efficient upscaling to huge output image sizes.

Upscaling.Tab.mov

We're pretty happy with the results!

image

4x scale, 4x_NMKD-Siax_200k upscale model, Deliberate_v5 SD1.5 model, KDPM 2 scheduler @ 30 steps, all other settings default

Requirements

You need 3 models installed to use this feature:

  • An upscale model for the first pass upscale
  • A main SD model (SD1.5 or SDXL) for the image-to-image
  • A tile ControlNet model of the same model architecture as your main SD model

If you are missing any of these, you'll see a warning directing you to the model manager to install them. You can search the starter models for upscale, main, and tile to get you started.

image

Tips

  • The main SD model architecture has the biggest impact on VRAM usage. For example, SD1.5 @ 2k needs just under 4GB, while SDXL @ 2k needs just under 9GB. VRAM usage increases a small amount as output size increases - SD1.5 @ 8k needs ~4.5GB while SDXL @ 8k needs ~10.5GB.
  • The upscale and main SD model choices matter. Choose models best suited to your input image or desired output characteristics.
  • Some schedulers work better than others. KDPM 2 is a good choice.
  • LoRAs - like a detail-adding LoRA - can make a big impact.
  • Higher Creativity values give the SD model more leeway in creating new details. This parameter controls denoising start and end percentages.
  • Higher Structure values tell the SD model to stick closer to the input image's structure. This parameter controls the tile ControlNet.

Custom Upscaling Models

You can now install and use custom upscaling models in Invoke. The excellent spandrel library handles loading and running the models.

Custom.Upscaling.Models.mov

spandrel can do a lot more than upscaling - it supports a wide range of "image to image" models. This includes single-image super resolution like ESRGAN (upscalers) but also things like GFPGAN (face restoration) and DeJPEG (cleans up JPEG compression artifacts).

A complete list of supported architectures can be found here.

Note: We have not enabled the restrictively-licensed architectures, which are denoted with a + symbol in the list.

Installing Models

We've added a few popular upscaling models to the Starter Models tab in the Model Manager - search for "upscale" to find them.

image

You can install models found online via the Model Manager, just like any other model. OpenModelDB is a popular place to get these models. For most of them, you can copy the model's download link and paste in into the Model Manager to install.

Nodes

Two nodes have been added to support processing images with spandrel - be that upscaling or any of the other tasks these models support.

image
  • Image-to-Image - Runs the selected model without any extra processing.
  • Image-to-Image (Autoscale) - Runs the selected model repeatedly until the desired scale is reached. This node is intended for upscaling models specifically, providing some useful extra functionality:
    • If the model overshoots the target scale, the final image will be downscaled to the target scale with Lanczos resampling.
    • As a convenience, the output image width and height can be fit to a multiple of 8, as is required for SD. This will only resize down, and may change the aspect ratio slightly.
    • If the model doesn't actually upscale the image, the scale parameter will be ignored.

Gallery Improvements

Thanks to @maryhipp and @chainchompa for continued iteration on the gallery!

  • Cleaner boards UI.
  • Improved boards and image search UI.
  • Fixed issues where board counts don't update when images are moved between boards.

Other Changes

  • Enhancement: When installing starter models, the description is carried over. Thanks @lstein!
  • Enhancement: Updated translations.
  • Fix: Model unpatching when running on CPU, causing bad/no outputs.
  • Fix: Occasional visible seams on images with smooth textures, like skies. MultiDiffusion tiling now uses gradient blending to mitigate this issue.
  • Fix: Model names overflow the model selection drop-downs.
  • Internal: Backend SD pipeline refactor (WIP). This will allow contributors to add functionality to Invoke more easily. This will be behind a feature flag until the refactor is complete and tested. Thanks to @StAlKeR7779 for leading the effort, with major contributions from @dunkeroni and @RyanJDick.

Installation and Updating

To install or update to v4.2.7rc1, download the installer and follow the installation instructions.

To update, select the same installation location. Your user data (images, models, etc) will be retained.

Missing models after updating from v3 to v4

See this FAQ.

Error during installation ModuleNotFoundError: No module named 'controlnet_aux'

See this FAQ

What's Changed

Full Changelog: v4.2.6post1...v4.2.7rc1

Contributors

lstein, weblate, and 8 other contributors
Assets 5
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