Dreambooth-SD-optimized VS stable-diffusion-webui

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.

* LLaVA model: I'll add more documentation. You are right Llava could not generate images. For image generation I don't have immediate plans, but checkout these projects for local image generation.

- https://diffusionbee.com/

- https://github.com/comfyanonymous/ComfyUI

- https://github.com/AUTOMATIC1111/stable-diffusion-webui

I would love to be able to have a native stable diffusion experience, my rx 580 takes 30s to generate a single image. But it does work after following https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki...

I got this up and running on my windows machine in short order and I don't even know what stable diffusion is.

But again, it would be nice to have first class support to locally participate in the fun.

In Auto1111, that just uses Image.blend. :)

https://github.com/AUTOMATIC1111/stable-diffusion-webui/blob...

I used SDXL in automatic1111 webui for both images. Now that I think about it, the procedure I described was how I made this one, but the one that looks like an illustration was done in two steps. I used the canny ControlNet as I said for the outer part of the logo to preserve the shape of the fonts, but I had to turn it off for the boot to give SDXL leeway to add detail and make it look more like a boot.

That said, please do learn coding and don't get discouraged when somebody says to learn PyTorch or recommends using a Jupiter notebook with no further information on how to translate the skill into images. I would highly recommend some short term goals. Get your feet wet by taking apart the UIs. The comfy API documentation is here and the A1111 API documentation is here. There is a difference in completeness, welcome to programming. Writing nodes or plugins is also a good way to jump into this world. Custom wildcard logic might be very attractive to you if you aren't the type that want to deal with a nested file structure to simulate logic.

Possibly Unprompted? https://github.com/AUTOMATIC1111/stable-diffusion-webui/discussions/8094

version: v1.6.1  •  python: 3.10.13  •  torch: 2.0.1+cu118  •  xformers: 0.0.20  •  gradio: 3.41.2  •  checkpoint: 6e8d4871f8