Dreambooth-SD-optimized VS Dreambooth-Stable-Diffusion

Hey guys im quite new to dream booth i tried the one in stabel diffusion but wasnt really satisfied with the output. Im lloking for a external dreambooth that could be started with anaconda but doesnt need 24 gb Vram i only have 12 Gb. I tried gammagec / Dreambooth-SD-optimizedbut he says you need at least 24 GB

Using this GitHub https://github.com/gammagec/Dreambooth-SD-optimized from this guide https://pastebin.com/xcFpp9Mr

I had pretty good results with 20 images of myself, 200 reg images and 6000 step using https://github.com/gammagec/Dreambooth-SD-optimized.

I use Automatic1111 for SD and then Dreambooth Optimized https://github.com/gammagec/Dreambooth-SD-optimized to do custom models.

Gammagec Dreambooth-SD-optimized - https://github.com/gammagec/Dreambooth-SD-optimized

I use this dreambooth repo to train the SD model. https://github.com/gammagec/Dreambooth-SD-optimized Here's the video that shows how to install it in very good detail. https://youtu.be/TwhqmkzdH3s He uses it to train in a face but you can use it to train in a style as well. I suggest taking about 15 or 20 detailed frames of the video and training it in as a style for the class name. You'll have to experiment with how many training steps to take. I suggest doing 1,000 steps at a time and testing out the model. Also don't leave the default "sks", the researchers forgot that that's a common acronym if you know what I mean. Do something like my_style1 so the model doesn't get confused with something else.

I'm using this guide: https://www.reddit.com/r/StableDiffusion/comments/xpoexy/yet_another_dreambooth_post_how_to_train_an_image/ to train locally with this repo https://github.com/gammagec/Dreambooth-SD-optimized on windows. Needs a 24gb card though.

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