auto-sd-paint-ext VS diffusers

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)

ShivamShrirao's Diffusers Pretrained diffusion models across multiple modalities.

Like the title say I'm trying to fine-tune a model to match a style of a popular manhwa. I'm using the ShivamShrirao Google Colab to accomplish this.

I am running the DreamBooth_Stable_Diffusion.ipynb notebook from ShivamShrirao locally on my machine. Let's say I have trained for 500 iterations and it hasn't converged yet. How do I make it resume training from that iteration so it can do another 500?

My understanding, based on messages from an (alleged) representative of colabs, is that the webui is the problem, not SD itself. This also seems to be the consensus in the comments section of other posts. I have not yet seen a link to colab based webui alternatives so here is something I found from a tutorial. I am certain that there are better alternatives. Anyone have a better idea? This will still probably be useful to other people like me who are just messing around.

I'm running ShivamShrirao's fork of diffusers; ran into a fp16 issue and had to patch in a fix from the main branch ( #1567 ).

I am running Shivam Stable Diffusion Jupyter notebook: diffusers/DreamBooth_Stable_Diffusion.ipynb at main · ShivamShrirao/diffusers · GitHub.

Are you using this one? https://github.com/S