ddetailer VS InvokeAI

Looks like it's a known issue. Looks like you'll need to remove the mmcv folder in your venv folder.

One way to avoid the inpainting issue is to use Ddetailer or Adetailer to auto-inpaint detected faces. I use the latter as I couldn't get ddetailer to work, but the fundamental feature is the same. It does a face-detection and inpainting pass after the initial generation (and hires fix), which means your first output already has the face fixed somewhat. And then you can go in to correct smaller details.

You can downgrade the mmdet https://github.com/dustysys/ddetailer/issues/41 or move to active fork https://github.com/Bing-su/dddetailer

Check also GitHub - dustysys/ddetailer It's not obvious how to adjust it's settings but it's specifically for detecting/segmentig persons and faces

use ddetailer my dude https://github.com/dustysys/ddetailer seems like is exactly what you need

Get DDetailer Makes faces super HD without having to go into "High Resolution Fix", like... everyone needs this, install it on extensions page by pasting the GitHub link.

I'm not sure if there is something like this, because you need to manually highlight the things you need to inpaint, but there was extension for auto-masking... Oh, it actually made for inpainting. https://github.com/dustysys/ddetailer or you can go to available tab in extensions.

Probably not, since I have no idea what you're talking about. I've just been using the models that InvokeAI (2.3, I only just now saw there's a 3.0) downloads for me [0]. The SD1.5 one is as good as ever, but the SD2 model introduces artifacts on (many, but not all) faces and copyrighted characters.

[0] https://github.com/invoke-ai/InvokeAI

I actually used the rocm/pytorch image you also linked.

I'm not sure what you're pointing to with your reference to the Fedora-based images. I'm quite happy with my NixOS install and really don't want to switch to anything else. And as long as I have the correct kernel module, my host OS really shouldn't matter to run any of the images.

And I'm sure it can be made to work with many base images, my point was just that the dependency management around pytorch was in a bad state, where it is extremely easy to break.

> Anyways, hopefully this PR fixes the immediate issue: https://github.com/invoke-ai/InvokeAI/pull/5714/files

It does! At least for me. It is my PR after all ;)

The data being flagged is not in that github repo, it's fetched from elsewhere and I don't fancy spending time looking for it. The alert is for 'Sirefef!cfg' which has been reported as a false positive with a bunch of other stable diffusion projects (https://www.reddit.com/r/StableDiffusion/comments/101zjec/trojanwin32sirefefcfg_an_apparently_common_false/, https://www.reddit.com/r/StableDiffusion/comments/xmhukb/trojan_in_waifudiffusion_model_file/, https://github.com/invoke-ai/InvokeAI/issues/2773 )

I haven’t tried it recently, but InvokeAI runs on Mac. Invoke. I used to run on my MacBook, but have since gotten a Win laptop.

There are already a number of local, inference options that are (crucially) open-source, with more robust feature sets.

And if the defense here is "but Auto1111 and Comfy don't have as user-friendly a UI", that's also already covered. https://github.com/invoke-ai/InvokeAI

https://github.com/invoke-ai/InvokeAI should work on your machine. For LLM models, the smaller ones should run using llama.cpp, but I don't think you'll be happy comparing them to ChatGPT.

Stable Diffusion. /r/stablediffusion There are many tutorials on how to set it up locally and use it. InvokeAI is the easiest way to set it up. https://github.com/invoke-ai/InvokeAI

InvokeAI