Dreambooth-Stable-Diffusion VS stable-diffusion-videos

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

Main Code: https://github.com/nateraw/stable-diffusion-videos/

So I've continued to experiment with how many papers I can fit into a single pipe and have them play nicely together. The images below were created by combining the panorama code from omerbt/MultiDiffusion with the ideas from albarji/mixture-of-diffusers. Also turns out nateraw/stable-diffusion-videos can be seen as a special case of a panorama (in latent space rather than prompt space).

https://huggingface.co/spaces/tomg-group-umd/pez-dispenser https://huggingface.co/spaces/AIML-TUDA/safe-stable-diffusion https://huggingface.co/spaces/AIML-TUDA/semantic-diffusion https://github.com/nateraw/stable-diffusion-videos

The goal is to make a (short) video out of a given first and last frame. It is similar to what this guy does (https://github.com/nateraw/stable-diffusion-videos (7sec example video half way down page)). But instead of starting and ending with a prompt, I want to start and end with 2 different frames.

Hey Y'all! We've been working on a tool that extends Nate Raw's Stable Diffusion Videos repo and makes it as easy as possible to use for artists and are having a competition this week to stress test the beta and see who can use it to make the most compelling short video (40 seconds max)

Of course! There might be a better process but mainly used: 1.) Nate Raw's repo for morphing between prompts https://github.com/nateraw/stable-diffusion-videos 2.) Google FILM interpolation to smooth out transitions https://github.com/google-research/frame-interpolation

There are directions in the readme and an example script.

This does exactly that - https://github.com/nateraw/stable-diffusion-videos