So, an important thing about stable diffusion is the models are trained on small images. 512x512 pixels is the standard size for most SD1.5 based models (768 for a few). SD2.x models can be either 512px or 768px, depending on the one chosen.
@ -237,7 +236,33 @@ Why do all the reroutes and color coding? Can't we connect directly from the mod
* besides, using stable diffusion is about making pretty pictures. Let's make pretty workflows, too!
## Expanding on Fixing
(Still writing this too)
Adding more nodes and increasing the HR-Fix is easy.
* Drag the ouput nodes to the right so there's more space.
* and decrease denoise a little. For this one, .450 is good.
* each ksampler in a HRF will decrease the noise
* though for latent space, about .2 is the lowest. Usually.
[here's the current workflow](basic-wf-vae-lora-latemt-upscale-x2.json)
More latent HRFs will gradually increase the output image while adding details. But let's stop here and add some pixel space HRFs. Onewards, noble steed!