[1] parrotchess.com, no longer available. Previous discussions: https://hn.algolia.com/?q=parrotchess.com

Comments URL: https://news.ycombinator.com/item?id=49910136

Points: 2

# Comments: 0

> Submit the original, unchanged photo.

> Do not change your photo using computer software, phone apps or filters, or artificial intelligence.

and many other countries have similar requirements.

EDIT: I just read the "Common Questions" that says: "This editor crops and centers the photo you provide and can replace the background. It does not invent or beautify a face." I guess that's not as bad then. Still mildly iffy and weird marketing though.

[1] https://travel.state.gov/en/passports/apply/help/photos.html

Adam Magyar and Jay Mark Johnson have line scan photos in fine arts as well, and they were in fact a big source of inspiration when I started out on my own line scan journey in 2017.

- https://www.magyaradam.com/wp/?page_id=368

- https://www.jaymarkjohnson.com/works

Seth Itow, Philomena, and Elm-chan both also have hobbyist line scan camera setups:

- https://www.sethitow.com/posts/2026-linescan/

- https://philo.gay/linecam/

- https://elm-chan.org/works/lcam/report.html (be sure to scroll down and click on the train pics)

There are also Japanese rail fans:

- https://kr64.seesaa.net/ with a bewilderingly huge collection of trains all over Japan,

And faux-line scan cameras using regular video cameras, stitching together thin chunks rather than 1 px columns:

- https://railfile.jp/

- https://x.com/yamakox/status/2089934720759144653

- https://kakeyama.image.coocan.jp/index.htm

- https://trains.jo-m.ch/#/trains/list

Line scan cameras are also commonly used for machine vision in the rail industry to inspect trains for damage and detect graffiti and stuff. And conversely, line scan cameras mounted on trains are used to inspect rails and tunnels.

By the way, I recognize your username as the person that Philo credits with "rewriting grindstone in idiomatic NumPy". That's super cool!

[1] https://github.com/FlamingSpork/grindstone/issues/1

[2] https://daniel.lawrence.lu/blog/2026-06-12-standalone-cnc-li...

[1] https://www.streetcar.org/about-sfmsr/

https://github.com/vitroid/TrainScanner

It converts a regular video into a line scan style photo. It works by stitching together small chunks rather than 1px thin slices, so the background has a repetitive texture rather than being smooth horizontal stripes. But at lower resolutions, it looks similar, especially if you pick a spot with a clean background. Also the trains turn out very detailed.

Example work by Kakeyama from Japan using this: https://kakeyama.fan.coocan.jp/tec/e5e8r.htm

Previously I've also used these full frame lenses:

- Myutron 50mm f/2.6 (Shinkansen N700A, SF Cable Car 2017)

- Voigtlander Nokton 58mm f/1.4 (Brisbane Queensland EMU)

- Samyang 135mm f/2 (Madrid AVE Class 102 and Shanghai maglev)

- Voigtlander Apo Lanthar 125mm f2.5 (Yamanote Line, CR400AF)

- Voigtlander Apo Skopar 90mm f/2.8 (London Tube photos)

- Voigtlander Ultron 35mm f/1.7 (Hong Kong trams)

and APS-C lenses:

- Cheecar 50mm f/1.2 (Osaka trains)

- Samyang 85mm f/1.8 CS (Caltrain)

https://i.dllu.net/swing_07_7668f7f16ff7ac2a.png

Also motorcycle cops:

https://commons.wikimedia.org/wiki/File:San_Francisco_Police...

- Line scan camera image processing: https://daniel.lawrence.lu/blog/2025-09-21-line-scan-camera-... Previous discussions:

  - https://news.ycombinator.com/item?id=44996938

  - https://news.ycombinator.com/item?id=46383593

  - https://news.ycombinator.com/item?id=46388084

- Line scan camera image processing 2: https://daniel.lawrence.lu/blog/2026-08-02-line-scan-camera-...

[1] https://github.com/mcneel

[1] https://github.com/huggingface/candle

Probably just taking photos with a really long telephoto lens would be good.

In theory, you'd use a telecentric lens [1], but then the lens would need to be bigger than the subject, which is not super feasible for a car-sized subject. I guess for line scan, the telecentric lens just needs to cover a small vertical strip of the car so it just needs to be really tall.

[1] https://en.wikipedia.org/wiki/Telecentric_lens

* better squares-in-circle packing for n = 31 and n = 34: https://github.com/dllu/packing and https://erich-friedman.github.io/packing/squincir/

* vibe coded CAD application (paused due to lack of quota on my $200/mo plan). Rather doubtful if GPT-6 Astra can one shot a correct B-rep kernel but whatever: https://github.com/dllu/viboceros

* ray traced chess demo: https://github.com/dllu/chess-rtx

In my experience, it varies widely by workload. Vision is great for some UI stuff but extremely terrible for my work, which involves visualizing connectivity and geometric stuff for road structure for autonomous vehicles. It can get super frustrating when I paste a screenshot and go "this polyline isn't connected when it should be" or "those polylines are self intersecting in an invalid way" and then the AI literally can't see what I'm talking about. It would have to then write debug code to dump out the coordinates of the polylines to convince itself that the bug even exists. Then it would often claim that it's fixed when it is clearly not.

I previously complained about GPT 5.6 Sol not being able to solve a simple "follow the lines" puzzle [1] without having to write custom Python code for it. GPT-6 Astra, however, is vastly improved, and could do it without writing Python. Still, for my work, it can occasionally struggle.

[1] https://news.ycombinator.com/item?id=49334444