Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

A Web UI for Stable Diffusion

github.com

Post reply on HN
Print view View original

91–100 of 148 posts

Re: A Web UI for Stable Diffusion

#91

Post by skipnup »

cloudking wrote: post #86

How does copyright work with output images? If someone runs the model on their own hardware, do they "own" the images generated? If 2 people generate the same image using the same prompt/seed, who "owns" the image?

Is it any different than Photoshop content aware fill? Or using a camera?

Nobody would ever think about Adobe or Nikon having copyright claims over your pictures. For me it's just a tool, the artistic part is providing a good description/base image, refining and choosing the best output.

Anyway, I'm not a lawyer and we probably live in different countries, so it'll be interesting to wait for the first lawsuit.

Re: A Web UI for Stable Diffusion

#92

Post by cthalupa »

cloudking wrote: post #86

How does copyright work with output images? If someone runs the model on their own hardware, do they "own" the images generated? If 2 people generate the same image using the same prompt/seed, who "owns" the image?

https://www.smithsonianmag.com/smart-news/us-copyright-offic...

In the US, AI generated art cannot be copyrighted.

Edit:

Some additional details.

The US also denied a copyright for one where the creator listed themselves, with the AI just being a co-creator.

https://www.reddit.com/r/COPYRIGHT/comments/vshypc/the_us_co... (Original article is paywalled, reddit post contains the relevant bits)

In particular: >“Even though you argue that there is some human creative input present in the work that is distinct from RAGHAV’s contribution, this human authorship cannot be distinguished or separated from the final work produced by the computer program,” the office stated.

The US does seem to be a bit of an outlier here. The above work was granted copyright in Canada and India.

In the EU, AI generated artwork is likely copyrightable: https://link.springer.com/article/10.1007/s40319-021-01115-0

The same for the UK: https://www.kilburnstrode.com/knowledge/ai/ai-musings/respon...

Edit2: I'm not a lawyer, this isn't legal advice, go contact one if you actually need legal advice here.

Re: A Web UI for Stable Diffusion

#93

Post by cal85 »

cthalupa wrote: post #92
cloudking wrote: post #86

How does copyright work with output images? If someone runs the model on their own hardware, do they "own" the images generated? If 2 people generate the same image using the same prompt/seed, who "owns" the image?

https://www.smithsonianmag.com/smart-news/us-copyright-offic... In the US, AI generated art cannot be copyrighted. Edit: Some additional details. The US also denied a copyright for one where the creator listed themselves, with the AI just being a co-creator. https://www.reddit.com/r/COPYRIGHT/comments/vshypc/the_us_co... (Original article is paywalled, reddit post contains the relevant bits) In particular: >“Even tho…

That’s one case, not a ruling about all AI generated art. It won’t be the same for every image involving AI in some way. What if you use AI to fill in a portion of an image, as with Adobe’s content aware fill? What if you use a series of SD steps but with a human selecting outputs and feeding them back in as inputs to get something else the AI could not have come up with on its own? The copyright conversation is only just beginning.

Re: A Web UI for Stable Diffusion

#94

Post by rassibassi »

MattRix wrote: post #71
bootsmann wrote: post #46

Earlier quoted context omitted.

You can think of it more like this: If I do 100 experiments of dropping stones at variable heights and measuring the time it takes for the stone to land on the ground I have enough datapoints to make a linear estimation of gravity by using linear regression. So based on my data I create a model that the time it takes for a stone to fall is sqrt(2h/9.81). Now if you want to figure out how long it takes for your stones…

This is exactly it. It’s pretty remarkable that it was trained on over 100 terabytes of images and yet the model has been distilled down to only 4gb.

Yes, and another reason for the small model size and the novelty of the underlying paper [1], is that the diffusion model is not acting on the pixel space but rather on a latent space. This means that this 'latent diffusion model' does not only learn the task at hand (image synthesis) but in parallel also a powerful lossy compression model via an outer auto encoder structure. Now, the number of weights (model size) can be reduced drastically as the inner neural network layers act on a lower dimensional latent space rather than a high dimensional pixel space. It's fascinating because it shows that deep learning at its core comes down to compression/decompression (encoding/decoding), with close relation to Shannon's Information Theory (e.g. source coding/channel coding/data processing inequality).

[1] https://arxiv.org/abs/2112.10752

Re: A Web UI for Stable Diffusion

#95

Post by cthalupa »

cal85 wrote: post #93
cthalupa wrote: post #92

Earlier quoted context omitted.

https://www.smithsonianmag.com/smart-news/us-copyright-offic... In the US, AI generated art cannot be copyrighted. Edit: Some additional details. The US also denied a copyright for one where the creator listed themselves, with the AI just being a co-creator. https://www.reddit.com/r/COPYRIGHT/comments/vshypc/the_us_co... (Original article is paywalled, reddit post contains the relevant bits) In particular: >“Even tho…

That’s one case, not a ruling about all AI generated art. It won’t be the same for every image involving AI in some way. What if you use AI to fill in a portion of an image, as with Adobe’s content aware fill? What if you use a series of SD steps but with a human selecting outputs and feeding them back in as inputs to get something else the AI could not have come up with on its own? The copyright conversation is only…

>That’s one case, not a ruling about all AI generated art

"Because copyright law as codified in the 1976 Act requires human authorship, the Work cannot be registered."

The actual ruling (and a similar USPTO discussions) are about AI generated art and talk extensively about it in the broad case. The stance of these organizations is that AI generated art is not copyrightable. I don't disagree that the line is blurred when you discuss content aware fill, where the AI is working on a portion of it, but the current use of SD, even img2img and multiple prompts, etc., quite clearly falls outside of human authorship as recognized by the US Copyright and Patent offices.

https://www.copyright.gov/rulings-filings/review-board/docs/... https://www.uspto.gov/sites/default/files/documents/USPTO_AI...

Might this change in the future? Possibly. But as it stands today, I would not make any plans that assume you can secure the copyright (in the US) to anything made with SD.

Edit: Going through and noting that I'm not a lawyer and this isn't legal advice, don't listen to some random on the internet for legal advice, get a lawyer if you need it.

Re: A Web UI for Stable Diffusion

#96

Post by fragmede »

TekMol wrote: post #70
user-one1 wrote: post #6

It can be run directly into google colab: https://colab.research.google.com/drive/1Iy-xW9t1-OQWhb0hNxu...

When I run it, I get "Your session crashed for an unknown reason."

Just click runtime -> run all again. There’s a weirdness where Python’s loader gets confused and the most effective fix is to crash the interpreter

Re: A Web UI for Stable Diffusion

#97

Post by DougBTX »

cthalupa wrote: post #95
cal85 wrote: post #93

Earlier quoted context omitted.

That’s one case, not a ruling about all AI generated art. It won’t be the same for every image involving AI in some way. What if you use AI to fill in a portion of an image, as with Adobe’s content aware fill? What if you use a series of SD steps but with a human selecting outputs and feeding them back in as inputs to get something else the AI could not have come up with on its own? The copyright conversation is only…

>That’s one case, not a ruling about all AI generated art "Because copyright law as codified in the 1976 Act requires human authorship, the Work cannot be registered." The actual ruling (and a similar USPTO discussions) are about AI generated art and talk extensively about it in the broad case. The stance of these organizations is that AI generated art is not copyrightable. I don't disagree that the line is blurred w…

> quite clearly falls outside of human authorship as recognized by the US Copyright and Patent offices.

I think these are answering a slightly different question, as they are asking if the AI itself can hold the copyright on the output. A bit like if someone tried to copyright an image and assign “Photoshop” as the author.

The question above is maybe closer to asking if the person using an ML model can get copyright on the output, in that case there is a person trying to own the copyright, so I suspect it would not be rejected so easily.

Re: A Web UI for Stable Diffusion

#98

Post by stavros »

CitrusFruits wrote: post #32
totoglazer wrote: post #24

Earlier quoted context omitted.

What settings? That seems faster than expected.

It was the defaults for the webui I used. Faster than I expected too, but the results were all legit. Edit: Got home and was able to double check. It's actually a solid 10 seconds per image with the following settings: seed:466520488 width:512 height:512 steps:50 cfg_scale:7.5 sampler:k_lms. Still quick enough for some fun, but could be annoying if you're need to do multiple iterations a minute.

Two minutes with my 1060, sadly.

Re: A Web UI for Stable Diffusion

#99

Post by rassibassi »

rassibassi wrote: post #94
MattRix wrote: post #71

Earlier quoted context omitted.

This is exactly it. It’s pretty remarkable that it was trained on over 100 terabytes of images and yet the model has been distilled down to only 4gb.

Yes, and another reason for the small model size and the novelty of the underlying paper [1], is that the diffusion model is not acting on the pixel space but rather on a latent space. This means that this 'latent diffusion model' does not only learn the task at hand (image synthesis) but in parallel also a powerful lossy compression model via an outer auto encoder structure. Now, the number of weights (model size) c…

Correction: the auto encoder is pre-trained :)

Re: A Web UI for Stable Diffusion

#100

Post by geuis »

fragmede wrote: post #80
geuis wrote: post #60

Earlier quoted context omitted.

I've been looking into this for the last 2 days. Unless you're running an M1 Mac or newer, you're SOL. Stable Diffusion is built on PyTorch. PyTorch mainly has been designed to work with Nvidia cards. However PyTorch added support for something called RocM like a year ago that adds compatibility with newer AMD cards. Unfortunately RocM doesn't support slightly older AMD cards in conjunction with intel processors. So…

Apple's MPS drivers supports AMD GPUs on MacOS

Just heard about MPS in another thread.
Post reply on HN