Hilarious post aside, I've been using Stable Diffusion to generate "ideas" in large volume by creating a lot of images from a single (very generic) prompt with very low accuracy/depth levels, then when I find something that might be interesting, I fire up img2img and iterate over that with better accuracy, resolution, and depth. The results are pretty amazing.

That's a great idea!

I've been curious, isn't img2img basically just more SD passes? Ie you generate something with 5 passes, then img2img just runs the other 95 over that to "complete" the image.

Basically, as far as I understand it (which is not much), txt2img generates a very rough blob from a prompt, then img2img does additional passes over that to refine it to something that has much higher quality. Is this incorrect?

I'm actually not sure how it works specifically because I don't know much about the technology behind it. All I know is that if I change the prompt (compared to the original prompt given by the txt2img script) and finetune the parameters I can get some *very* differing results that only keep a certain "style" or vibe.

For example I generated [0] as my base image, I passed it into a dithering filter to make it look more "retro" and got [1] (was going for retro PC98 visual novel style backgrounds), and then [3] are all new results generated from it (I added stuff like "village" or "trees" etc in the new prompt and also made the resolution widescreen). You can tweak parameters like the prompt, the depth (ddim), the "strength" of the original image, and the "scale" (not sure what it is but it does change things around). Then you can play with that and even iterate on more images.

[0] https://upload.i.ng/file/goaltendersgrievousSumter/seed_6436...

[1] https://upload.i.ng/file/overstatementrearwardsplighting/dit...

[2] https://twitter.com/xMorgawr/status/1564271156462440448