Comment on Not likely to be AI-generated or Deepfake
TheRealKuni@lemmy.world 3 weeks agoEither that’s not true of AI images or it’s true of all images. There aren’t answers that simple to this. Pixels are pixels.
What? That’s some extreme logic.
First of all why would it be true if all images? Real photos would have variance of contrast and color in different ways.
I was slightly off anyways it was about a eeaging contrast
Instead of engaging the conversation you just say pixels are pixels? Luke that means something smart?
My point is that AI images don’t differ significantly enough from non-AI images. “AI images” is an extremely broad category.
If you are narrowing that category to, say, “all Dall-E images” or “all Midjourney images” or something, MAYBE. They tend to have a certain “look.” But even that strikes me as unlikely, and those are just a slice of the “AI images” pie.
As someone who has played around with Stable Diffusion and Flux, the “average color” of an image can vary dramatically based on what settings and models you’re running. AI can create remarkably real-looking images with proper variance in color and contrast, because it’s trained on real photos. Pixels, as I said, are pixels.
That’s not to mention anime or sketch or stained glass or any other medium imitation. And of course, image-to-image with in-painting, where only parts of an image are handled by the AI.
My point is that if there were overtly simple answers like, “all AI images average their color to a beige,” then there wouldn’t be all this worry about AI images. It would be easy to detect them. But things aren’t that simple, and if you spend a small amount of time looking into the depth that generating AI images has gained even in the last year, you’d realize how absurd a simple answer like that is.
So because you “make” AI generated images you are saying that they are magical and don’t follow the rules of their generation?
They are based on noise maps and inferred forwards from there. They leave a history in the pixels it’s how lots of people are detecting them.
Just because it’s trained on real photos does not mean it’s still a real photo. Just cause it looks fine doesn’t mean there isn’t stuff true beneath it.
In the video I linked they even talk about how the red blue green maps have the same values cause it started with a colorless pixel anyways. A real sensor doesn’t do that.
I worked with photographers and in Photoshop and did what you think you are doing. Working with images and pixels are not just pixels. That means nothing. Dogs are just dogs. There are still different breeds and types of dogs.
So because you “make” AI generated images you are saying that they are magical and don’t follow the rules of their generation?
That’s what you got from what I wrote?
There’s nothing “magical,” but the variety of AI images that can be produced belies the simplicity of their detection. Which has been my point this whole time.
They are based on noise maps and inferred forwards from there.
There are an infinite number of methods to diffuse noise into an image, and changes to any one of a wild number of variables produces a different image. Even with the same seed and model, different noise samplers can produce entirely different types of images. And there are a LOT of different samplers. And thousands of models.
Then there are millions of LORAs that can add or remove concepts or styles. There are ControlNets that let a generator adjust other features of the image generation, from things like poses to depth mapping to edge smoothing to color noise offsets and many many many more.
The number of tweaks that can be made by someone trying to generate a specific concept is insanely high. And the outputs are wildly different.
I don’t pretend to be an expert in this subject, I’ve barely scratched the surface.
In the video I linked they even talk about how the red blue green maps have the same values cause it started with a colorless pixel anyways. A real sensor doesn’t do that.
No, they give an extremely simple explanation of how noise maps work, and then speak as if it were law, “You’ll never see an AI image that’s mostly dark with a tiny little bit of light or mostly light with a tiny little bit of dark.” Or “You won’t have an AI photo of a flat sunny field with no dark spots.”
But that’s simply not true. It’s nonsense that sounds simple enough to be believable, but the reality isn’t that simple. Each step diffuses further from the initial noise maps. And you can adjust how that happens, whether it focuses more in lighter or darker areas, or in busier or smoother areas.
Just because someone on YouTube says something with confidence doesn’t mean they’re right. YouTubers often scratch the surface of whatever they’re researching to give an overview of the subject because that’s their job. I don’t fault them for it. But they aren’t experts.
(Neither am I, but I know enough to know they don’t know what they’re talking about at depth.)
None of the things they say in that video as though they are law or fact are things that haven’t already been thought of by people who know far more about the subject than these YouTubers (or me).
I did mention earlier that this sort of thing might be true for Dall-E or Midjourney or other cheap/free online services with no settings the user can tweak. AI images generated with as few steps as possible, with as little machine use as possible. They will be easier to spot, more uniform. But those aren’t all there is of AI images.
Another thing to consider: this technology is, at any given moment, at the worst it’s going to be going forward. The leaps and bounds that have been made in image diffusion even in the last year is remarkable. It is currently, sometimes, difficult to detect AI images. As time goes on, it will become harder.
(Which your video example even says.)
vithigar@lemmy.ca 3 weeks ago
It is absolutely not true of all AI images. I’d be surprised if it’s even true about most AI images.
Krauerking@lemy.lol 3 weeks ago
Just saying that because you feel like it’s true or because you’ve participated in that line of thought for even 5 seconds?
AI images come from a noise map, it’s true cause they generate from it in a consistent manner.
vithigar@lemmy.ca 3 weeks ago
I’m saying it because it’s not only obvious with even a moments thought (you can literally just ask it for an entirely red image or whatever), but also because it’s easily provable.
Prompt: “Under the sea”
Image:
Image
Average pixel colour:
Image
Prompt: “a man with red hair wearing a red coat standing in front of a red background”
Image:
Image
Average pixel colour:
Image
So I ask you the same question. Did you just say that because you felt like it was true?
Krauerking@lemy.lol 3 weeks ago
The average brightness values of those are both middle of the road grey. Sorry I should have rephrased as I misspoke calling it beige but the point still stands that has the most average toned color.
If you look they are middling around 50-60% where as a similar red photo intake would likely have a higher contrast and an average color with a higher brightness.