ddetailer VS kohya_ss

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.

Many of the options are explained here https://github.com/bmaltais/kohya_ss/wiki/LoRA-training-parameters

training in BF16 might solve this issue from what I saw in this ticket. I know other people ran into the issue too https://github.com/bmaltais/kohya_ss/issues/1382

for lycoris loras you can use the command-line script from the kohya-ss repo https://github.com/bmaltais/kohya_ss/blob/master/networks/merge_lora.py i have an older version checked out from late july, it had a separate merge_lycoris.py for for this purpose, it's probably unified now in a single file

I usually do that with kohya_ss, a tool made for making LoRAs and finetunes. It might be a bit of a pain to set up just to do this one task, but if nobody gives you an easier method, look into it. https://github.com/bmaltais/kohya_ss

After that, make your staging directory, and do the git clone https://github.com/bmaltais/kohya_ss.git, and navigate inside of it. Now, here's where things can become a pain. I used pyenv to set my system level python to 3.10.6 with pyenv global 3.10.6, though you can probably just use "local" and do it for the current shell. You NEED it to be active however before you set up your venv. If you do python --version and get 3.10.6, you're ready for this next part. Make your venv with python -m venv venv. This is the simplest way, it'll create a virtual environment in your current folder named venv. You'll do a source venv/bin/activate and then do which python to make sure it's using the python from the venv. Now for the fun part. The included setup scripts have been flaky for me, so I just went through the requirements and installed everything by hand. I'm going to do this guide right now for nvidia, because I just got a 4090 for this stuff. If this ends up working well for others and there's demand, I'll try to reproduce this for AMD (But I'll be honest, I got an nvidia card because bitsandbytes doesn't have full rocm support, nor do most libraries, so it's not very reliable). After installing everything and testing it works at least at a basic level for dreambooth training, my finished requirements.txt for pip is as below:

Earlier I created a post where I asked for recommendations for LoRA model training tutorials. The first one I looked at used the kohya_ss GUI. That GitHub repo already has two tutorials, which are quite good, so I ended up using those:

I have tried my best to research this issue and have not come up with much. It is obvious that its a backend issue right? The guides that I used https://github.com/bmaltais/kohya_ss and https://github.com/pyenv-win/pyenv-win/

I am training on a 12GB 3060 using kohya_ss. Is there a setting or something I'm missing?