upscayl VS Dreambooth-Stable-Diffusion

Windows has caused us a lot of issues with Upscayl (https://upscayl.org).

I personally do not use Windows but most of our errors are reported by Windows users where sometimes path parsing is a problem or the drivers mess up vulkan configuration.

> I guess yesterday's science fiction is now our reality.

That's actually what's written on https://upscayl.org, "From Science Fiction to Reality" haha

that website? No, I just used upscayl with the Digital Art preset

Upscayl, I've used it before, it's great

You can use Upscayl on pc and SuperImage on android to enhance your image so you don't have to find the hd version, both the applications uses you device's gpu to enhance your image.

might as well just run upscayl locally then. https://github.com/upscayl/upscayl

Instead of finding images that are already FullHD, I've found an open source software for image upscaling which seems to work very well with digital art/styles similar to something like Studio Ghibli, which is the style as was going for, so works great for me!

Considering a 4080RTX for AI tools performance in the future, noticed a big performance gap in upscayl, while using a rtx card vs non rtx https://github.com/upscayl/upscayl

Here is what I used: https://github.com/upscayl/upscayl

I did search online for an answer, but I am a PC noob, I didn't know what to do when I found this solution in this link: https://github.com/XavierXiao/Dreambooth-Stable-Diffusion/issues/113

Do you know some projects or guided tutorials that could help me? How many drawings with the desired style I should then have to give to train the AI model? I found Dreambooth on Stable Diffusion but it seams to be for another use case.

This seems to be an issue with the code and or the environment itself. There is an open bug for this where some suggestions are p provided by others on how to fix. https://github.com/XavierXiao/Dreambooth-Stable-Diffusion/issues/47

Could you provide some more detail on how this works? Did you just use this GitHub repository or did you put together your own implementation?

I think the best way to do this would be to train Dreambooth on a number of photos of Ray Liotta first, and use Stable Diffusion instead. https://github.com/XavierXiao/Dreambooth-Stable-Diffusion

Dreambooth. There are other ways, but that is the gold standard. It takes even more Vram than regular stable diffusion, so if you don't have a very beefy card (e.g. 4090 with 25 GB VRAM) various websites let you do it onlin for a small fee. You then download a new model that has all the old stuff (e.g.the 4 gigabyte SD 1.5 file) plus your new images. Like I said, there are other ways that are easier, but when people show great results they are usually talking about Dreambooth.

THE CODE (unofficial implementation, for the exact wording stating how little images you need read the paper) is designed with extremely little data in mind. I don't know how else to phrase it dude, do you think the training is a magic black box that runs with snail neurons? If you train a dreambooth model the jupyter ide makes calls to python files, those are the files. That is the code