auto-sd-paint-ext VS fast-stable-diffusion

It makes more sense to embed stable diffusion capabilities into well-established image editors such as Gimp, Photoshop, Krita, or Figma, which come with layered, non-destructive functionalities, rather than attempting the opposite approach.

https://github.com/Interpause/auto-sd-paint-ext

You might be interested in knowing that Krita has a SD plug in that I've found works quite well if you're willing and able to install and run SD locally. Krita is now my primary art program. https://github.com/Interpause/auto-sd-paint-ext

GitHub - Interpause/auto-sd-paint-ext: Extension for AUTOMATIC1111 to add custom backend API for Krita Plugin & more

Yep, Krita has a SD plugin too ( https://github.com/Interpause/auto-sd-paint-ext ) but probably not as good as this Photoshop one yet.

Again in my humble opinion, however, it's nice to be able to choose (at least if you're willing to pay the subscription costs) among different models and algorithms. Use whatever suits best your needs or your ideas. I personally prefer SD's versatility, and the workflows enabled by "being able to get my hands on all the parameters", like sampler selection, CFG scale, inpainting and other stuff (have you tried InvokeAI's unified canvas or Automatic1111's Krita plugin?). Not to mention the ability to do progressive and potentially infinite upscaling of an image (Automatic1111's "SD upscale" script or InvokeAI's "Embiggen").

I have a simple question that apparently i cant seem to figure out for the past like 12 hours, im using the https://github.com/Interpause/auto-sd-paint-ext auto extension for the krita plugin, and im simply just trying to inpaint creatures and just general things into a scene, but no matter what i do, the result is nothing like it, i followed the inpainting tutorial they have listed on github (New layer from visible) then make a new layer to paint the mask on, tried all fill methods with different steps, im fairly new to all of this and what not, im using a custom model checkpoint btw if that matters (protogen 5.8)

I tried using TheLastBen's fast dreambooth trainer. I managed to train a ckpt file but I can't run it.

You have a colab from ThelastBen It uses to be thes best at the time when auto1111 was working in google colab free. https://github.com/TheLastBen/fast-stable-diffusion

Using https://github.com/TheLastBen/fast-stable-diffusion

This repo offers a template how to start with SD on runpod https://github.com/TheLastBen/fast-stable-diffusion. But I know how to code, si I made my own solution.

I can confirm I'm using the latest version of the colab notebook of this repo (https://github.com/TheLastBen/fast-stable-diffusion). Anyone can point to any solutions to this problem? Thanks in advance!

TheLastBen's Fast DB SD Colabs, +25-50% speed increase, AUTOMATIC1111 + DreamBooth

CalledProcessError Traceback (most recent call last) in () 182 wget.download('https://github.com/TheLastBen/fast-stable-diffusion/raw/main/Dreambooth/det.py') 183 print('Detecting model version...') --> 184 Custom_Model_Version=check_output('python det.py '+sftnsr+' --MODEL_PATH '+MODEL_PATH, shell=True).decode('utf-8').replace('\n', '') 185 clear_output() 186 print(''+Custom_Model_Version+' Detected')

have you tried https://github.com/TheLastBen/fast-stable-diffusion ?