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Sort of a disclaimer: don't dive headfirst into a nightly build if you're planning to use it for your currect project which is already past its deadline - you'll have a bad day. This is not a production-ready user-friendly software :D

ATTENTION!  16GB VRAM NVIDIA GPU is required for local run, or colab pro with a high ram env. You may be able to run it on a smaller amount of VRAM, but I haven't tested it and can not confirm how low you'll have to go with your settings, so please join discord and ask around before subscribing.


4.04 - Isn't it the best time for a post :D

This release has some key features: TemporalNet, Reconstructed Noise, GUI additions/cleanup.

Notebook download - https://www.patreon.com/posts/81017961

Changelog: 

  • add predicted noise mode (reconstruction / rec) from AUTO111 and https://github.com/AUTOMATIC1111/stable-diffusion-webui/issues/736
  • add prompt schedule for rec
  • add cfg scale for rec
  • add captions support to rec prompt
  • add source selector for rec noise
  • add v1/v2 support for rec noise
  • add single controlnet support for rec noise
  • add multi controlnet to rec noise
  • add rec steps % option
  • add rec noise to gui
  • add TemporalNet from https://huggingface.co/CiaraRowles/TemporalNet
  • add temporalnet source selector (init/stylized)
  • skip temporalnet for 1st frame
  • add masked guidance toggle to gui
  • add masked diffusion toggle to gui
  • add softclamp to gui
  • add temporalnet settings to gui
  • add controlnet annotator settings to gui
  • hide sat_scale (causes black screen)
  • hide inpainting model-specific settings
  • hide instructpix2pix-scpecific settings


TemporalNet

TemporalNet is a ControlNet, which is intended to be used for stabilizing img2img series by using previous frame as input. You can use it together with other ControlNets in MultiControlNet mode. 


GUI -> Controlnet - temporalnet_source

It uses previous frame for better temporal stability. You can either use raw init video or stylized frame as input.


GUI -> Controlnet - temporalnet_skip_1st_frame

It will not work during the 1st frame by default, because it relies on previous frame. You can force it to be enabled during the 1st frame render by disabling this checkbox, it will then use the 1st raw video frame as it's image input.


Reconstructed noise 

(aka img2img alternative script from AUTO1111)

GUI -> diffusion -> reconstructed noise 

Diffusion models generate (denoise) images from random noise. During the img2img process we inject out init image somewhere halfway the denoising, so we need to add some random noise on top of it for the model to reconstruct it correctly. 

This introduces temporal inconsistency due to the randomness of the noise we add. 

One of the most elegant solutions to this porblem is using reconstructed noise instead of a random one. We take out init image, reverse sample it with out model, and get a very specific noise pattern. Given out model and settings this noise can be used to exactly reconstruct the init image. This means, that if we use this noise during our img2img process, the temporal inconsistency should be much lower than with random noise, as it's stronly related to our init image. 


use_predicted_noise:  enable the feature. won't work with fixed_code enabled


Rec Prompt: 

reconstruction prompt. You need this prompt to describe the scene without the style you're applying in the main prompt. Can use {caption} 

For example, if my main prompt is "a beautiful village by salvador dali", the reconstruction prompt should be "a beautiful village".


rec_cfg - reconstruction cfg_cale. keep low, between 1-1.9

rec_randomness - add random noise to reconstrcuted noise. 0 - no random, 1 - full random, no rec noise

rec_source - image used to reconstruct the noise from.

rec_steps_pct - % of current frame's total steps used for reconstruction. 1 - 100%, most accurate/slowest. 0.5 is okay for starters.



GUI updates

Model-specific settings are now only shown when using the respective model version. For example, image_scale and inpainting options are not visible unless you use instructpix2pix or inpainting model.

Added numerous frequently used settings to GUI. Some of the rarely used settings (like masked guidance and masked callback inner tweaks) are still left out of the GUI to keep it relatively clean.


Notebook download - https://www.patreon.com/posts/81017961

A reminder:

Changes in GUI will not be saved into the notebook, but if you run it with new settings, they will be saved to a settings.txt file as usual.

You can load settings in misc tab.

You do not need to rerun the GUI cell after changing its settings.

Local install guide:
https://discord.com/channels/973802253204996116/1067887206125015153/1067888756910215278
https://github.com/Sxela/WarpFusion/blob/main/README.md

Youtube playlist with settings:
https://www.youtube.com/watch?v=wvvcWm4Snmc&list=PL2cEnissQhlCUgjnGrdvYMwUaDkGemLGq

For tech support and other questions please join our discord server:
https://discord.gg/sayE6j2sdP

Discord is the preferred method, because it is nearly impossible to provide any decent help or tech support via Patreon due its limited text formatting and inability to add screenshots or videos to comments or DMs.
Error reports in comments will be deleted and reposted in discord.


Files

Stable WarpFusion v0.10.0 - TemporalNet, Reconstructed Noise (run 137 :D)

Vid by Ksenia Bonum Settings: https://pastebin.com/zfeqGWDd Notebooks: https://www.patreon.com/sxela

Comments

Kyle McLean

I see. I had assumed it was for M tier as get email notifications about it

sxela

I usually attach settings to YouTube demos, you can paste them into a txt file and load it into gui