I haven't been tested for many years, but I assume I have lost this type of depth perceptiion due to monovision after cataract surgery. I still have functional depth perception, but it must rely on other clues these days. And I still can't see stereoscopic images.
At least there are tools now that can undo the process by which these images are produced.
I found that the π and ∞ stereograms were easier for me than the graph ones, as it's easier to snap to focus once you recognise the general outline of the shape. The graph ones were a bit harder for me, although that may just be the colours used.
Popular enough to be on Seinfeld.
https://youtu.be/Uy9D0lO_0y0?t=38&si=f9zczm_noVd9hsmN
“Computers make these.. big computers”
Never been able to see them, but my eves have different enough vision that it is hard to make them work together at certain distances.
This was real incredible - no need to focus again - it is like living in this hidden world.
If you never experienced this I recommend to try it - at least for me it was a wow moment.
“What kind of SUV is that? He can’t mean… Oh, he does…! Holy s**t”
Also, thanks for the reminder to update my cv X-D
It’s unfortunate that so many humans were initially retired, but it was also helpful in motivating the population to finally figure out Magic Eye.
The kind of weird thing is that you can achieve the same effect with any repeated pattern - floor tiles, a fence post, etc. But there's no underlying illusiory image, so you just see basically the same thing but everything else is focused wrong.
Meaning, maybe GPT can't (yet) see magic eye images, but it shouldn't have trouble building itself a prosthetic that allows it to see them.
And these were easy. The first one literally took 15 seconds to "drop in." The second maybe ten. The third was near-instant. The only one that gave me any trouble was the continuous function one like an egg crate, with no sharp edges, just dropping down and up. That took maybe twenty seconds, and once I recognized what I was looking for, it was easy.
So has the technique changed/improved? Or has my brain changed?
And there is definitely a difference between them. If you try to view a cross view image using parallel view, it will look weird and not be easy to focus. Maybe the egg crate image was different?
Here's a quick test: https://i.redd.it/g5ilwgk99r781.jpg
Parallel view is easy for me but it takes a bit of effort for me to see cross view. For cross view, I start by looking cross-eyed at my nose and then try to see the image without fully uncrossing my eyes.
When I try to relax my eyes to look past the screen to start the parallel view (I think that's how it is done?) the image is too blurry to resolve. When I let my eyes adjust that, they fall apart to the separate images.
To me these all look like they're reversed from what this says, like they're further away from me behind the flat part.
People have pointed out that these are "straight eye" rather than "cross eye" ones. So my theory is on a big screen these are too wide for my eyes or something. I can always go cross eyed (by looking at my nose), but I probably can't go "wide eyed".
It is the herman2 entry here: http://www.ioccc.org/years.html#2001
Note that the source code is itself such an image.
wget https://www.ioccc.org/2001/Makefile
wget https://www.ioccc.org/2001/herrmann2.c
wget https://www.ioccc.org/2001/herrmann2.cup
wget https://www.ioccc.org/2001/herrmann2.hint
wget https://www.ioccc.org/2001/herrmann2.ioccc
cat herrmann2.hint #instructions
make herrmann2
./herrmann2 < herrmann2.ioccc
My mind is boggled. I get the basics of how autostereograms work, but the fact that it works so well with ASCII text is mindblowing.Edit: If you're lazy, I made a quick Gist that does the above, so you can just do
curl https://gist.githubusercontent.com/justusthane/a8c27c72350793ac452b86cc665a268b/raw/72aa6bf37689ea0cbbb70fa70fbd758c3a1fde3a | bash
(Obligatory "It's not safe to pipe internet stuff into a Shell" disclaimer)Edit: found this https://piellardj.github.io/stereogram-solver/ , it works well for single layer images; but it isn’t great for 3d surfaces. Another one, though not online, seems better: https://github.com/MikhailPedus/AutostereogramSolver
[1]: https://www.vexels.com/blog/stunning-3d-effect-with-gif-2-fr...
Almost think textbooks should utilize images like these, worked very well.