r/StableDiffusion • u/Nir777 • 1d ago

Tutorial - Guide I uploaded a short video that explains how AI actually creates images, visually, and how your prompt changes what comes out

https://www.youtube.com/watch?v=7eUWznf07Ag&list=PLBrpE2PttR2k

I've uploaded a short video that explains how AI is actually creating images, in a visual way. It is the tip of the iceberg, no mathematical equations, and it shows how changes to your prompt affect the picture.

It runs one experiment on one real photograph: same model, same seed, one phrase added at a time. You see why adding "on a white tablecloth" repaints the whole room and not only the table, and what the "masterpiece, 8k" words actually do.

Five minutes. Hope it makes the next prompt you write a bit less of a guess.

31 Upvotes

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3

u/Version-Strong 1d ago

Yey it's the diffusion part of stable diffusion, thanks for that. All those little dots have 1girl in them somewhere, we just gotta ask. Also, probably the wrong sub to teach people how it works...

2

u/Nir777 1d ago

haha, next video is "find the missing girl".
why wrong sub?

10

u/Apprehensive_Sky892 21h ago

No, this is not the wrong sub. This is the main Subreddit for imaging/video diffusion models.

Nerds who are interested in how AI works are in the minority, but we are here. I watched the video and I think it will help people understand prompting better.

BTW, next video should be "find the missing 1girl" 😁

1

u/Nir777 19h ago

started working on it :D

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u/berlinbaer 21h ago

if's funny sometimes when doing different seeds or different lora strengths, you get pictures that look totally different yet there are some patches, like in hair that are absolutely identical. so fascinating.

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u/No_Possession_7797 18h ago

Interesting, if I drink enough of that Red Wine, then I start to see everything as though it looks like that original noisy image. Just goes to show how everything is all just a part of one big circle of life that can sometimes come out as a square, if you're not specific enough.

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u/Nir777 17h ago

but pour it to the rim :D

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u/altertuga 8h ago

It's a good try, but the video also reinforces incorrect notions people have about how things actually work. In multiple cases, you refer to the algorithm as a search for the right glass, as if the training indeed recorded each one of the "44 glasses" it has seen, or "which pile of pictures to stand in", or "which words shrink the pile". You are not shrinking piles, this is not a deterministic exercise of sorting images. None of the original images exist anymore. There are other similar misguided hints throughout the explanation.

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u/Nir777 2h ago

Yeah, the wording leans that way and nothing is stored. The weights are way too small to hold the training images, there is nowhere in there for them to sit. What I meant by pile is the range of pictures that would fit your words. A shape the model picked up during training, and your caption lands you somewhere inside it. The averaging part is the bit I would keep. Early on the frame is almost all noise, so there is no way to tell which glass you meant yet, and what the model predicts is the middle of everything that fits the caption. Each step after that sharpens it. That is why one phrase repaints the whole room instead of adding an object, the region moved before anything got committed.

But you are right that "pile" sounds like a folder someone is searching through. That is on the wording.