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

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)

* LLaVA model: I'll add more documentation. You are right Llava could not generate images. For image generation I don't have immediate plans, but checkout these projects for local image generation.

- https://diffusionbee.com/

- https://github.com/comfyanonymous/ComfyUI

- https://github.com/AUTOMATIC1111/stable-diffusion-webui

I would love to be able to have a native stable diffusion experience, my rx 580 takes 30s to generate a single image. But it does work after following https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki...

I got this up and running on my windows machine in short order and I don't even know what stable diffusion is.

But again, it would be nice to have first class support to locally participate in the fun.

In Auto1111, that just uses Image.blend. :)

https://github.com/AUTOMATIC1111/stable-diffusion-webui/blob...

I used SDXL in automatic1111 webui for both images. Now that I think about it, the procedure I described was how I made this one, but the one that looks like an illustration was done in two steps. I used the canny ControlNet as I said for the outer part of the logo to preserve the shape of the fonts, but I had to turn it off for the boot to give SDXL leeway to add detail and make it look more like a boot.

That said, please do learn coding and don't get discouraged when somebody says to learn PyTorch or recommends using a Jupiter notebook with no further information on how to translate the skill into images. I would highly recommend some short term goals. Get your feet wet by taking apart the UIs. The comfy API documentation is here and the A1111 API documentation is here. There is a difference in completeness, welcome to programming. Writing nodes or plugins is also a good way to jump into this world. Custom wildcard logic might be very attractive to you if you aren't the type that want to deal with a nested file structure to simulate logic.

Possibly Unprompted? https://github.com/AUTOMATIC1111/stable-diffusion-webui/discussions/8094

version: v1.6.1  •  python: 3.10.13  •  torch: 2.0.1+cu118  •  xformers: 0.0.20  •  gradio: 3.41.2  •  checkpoint: 6e8d4871f8