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A Web UI for Stable Diffusion

github.com

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Re: A Web UI for Stable Diffusion

#21

Post by sC3DX »

jrm4 wrote: post #17

So, and this is an ELI5 kind of question I suppose. There must be something going on like "processing a kazillion images" and I'm trying to wrap my head around how (or what part of) that work is "offloaded" to your home computer/graphics card? I just can't seem to make sense of how you can do it at home if you're not somehow in direct contact with "all the data?" e.g. must you be connected to the internet, or "stable…

What you interact with as the user is the model and its weights.

The model (presumably some kind of convolutional neural network) has many layers, every layer has some set of nodes, and every node has a weight, which is just some coefficient. The weights are 'learned' during the model training where the model takes in the data you mention and evaluates the output. This typically happens on a super beefy computer and can take a long time for a model like this. As images are evaluated the output gets better the weights get adjusted accordingly.

Now we as the user just need the model and the weights!

Re: A Web UI for Stable Diffusion

#22

Post by Ckalegi »

ducktective wrote: post #15

It seems Midjourney generates better results than SD or Dall-E. What's with the "hyper resolution", "4K, detailed" adjectives which are thrown left and right, while we are at it?

The metadata and file names of the images in the source data set are also inputs for the model training. These keywords are common tags across images that have these characteristics, so in the same way it knows what a unicorn looks like, it also knows what a 4k unicorn looks like compared to a hyper rez unicorn.

Re: A Web UI for Stable Diffusion

#23

Post by totoglazer »

drexlspivey wrote: post #11
smrtinsert wrote: post #7

I have a 6gb 1660ti, barely holding on. Is a new 12gb card good enough for now, or should I go even higher to be safe for a few years of sd innovation?

How is M1/M2 support for SD? Is there a significant performance drop? Presumably you would be able to buy a 32GB M2 and be future proof because of the shared memory between CPU/GPU.

There was a long thread last week. It’s honestly pretty good if you follow the instructions. 30-40 seconds/image.

Re: A Web UI for Stable Diffusion

#24

Post by totoglazer »

CitrusFruits wrote: post #14
smrtinsert wrote: post #7

I have a 6gb 1660ti, barely holding on. Is a new 12gb card good enough for now, or should I go even higher to be safe for a few years of sd innovation?

I'm using it with a 2070 (4 year old card with 8gb vram) and it takes about 5 seconds for a 512x512 image. It's been plenty fast to have some fun, but I think I'd want faster if it was part of a professional work flow.

What settings? That seems faster than expected.

Re: A Web UI for Stable Diffusion

#26

Post by dwohnitmok »

jrm4 wrote: post #17

So, and this is an ELI5 kind of question I suppose. There must be something going on like "processing a kazillion images" and I'm trying to wrap my head around how (or what part of) that work is "offloaded" to your home computer/graphics card? I just can't seem to make sense of how you can do it at home if you're not somehow in direct contact with "all the data?" e.g. must you be connected to the internet, or "stable…

This is the main reason why attempts to say that these sorts of AI are just glorified lookup tables, or even that they are simply tools that mash together a kazillion images together are very misleading.

A kazillion images are used in training, but training consists of using those images to tune on the order of ~5 GB of weights and that is the entire size of the final model. Those images are never stored anywhere else and are discarded immediately after being used to tune the model. Those 5 GB generate all the images we see.

Re: A Web UI for Stable Diffusion

#27

Post by schleck8 »

ducktective wrote: post #15

It seems Midjourney generates better results than SD or Dall-E. What's with the "hyper resolution", "4K, detailed" adjectives which are thrown left and right, while we are at it?

Those are prompt engineering keywords. SD is way more reliant on tinkering with the prompt than midjourney

https://moritz.pm/posts/parameters

Re: A Web UI for Stable Diffusion

#29

Post by ghilston »

wyldfire wrote: post #8
nowandlater wrote: post #2

This is the one I've been using https://github.com/sd-webui/stable-diffusion-webui . docker-compose up , works great.

I like this one but had some trouble with using img2img. Maybe my image was too small (it was smaller than 512x512). Failed with the same signature as an issue that was closed with a fix.

I am mobile, but there's an issue reported on github about img2img

Re: A Web UI for Stable Diffusion

#30

Post by password4321 »

filiphorvat wrote: post #12
wyldfire wrote: post #9

Earlier quoted context omitted.

It sounds like there's forks that are able to work with But yeah the next generation of models would probably capitalize on more memory somehow.

People have reported that this repo even works with 2gb cards if you run it with --lowvram and --opt-split-attention.

Yes, the amount of VRAM doesn't seem to be as much of a limitation anymore. However, processing power is still important.
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