Search all text in New York City (alltext.nyc)

hah, it can find all the KEST GAK stickers now: https://www.alltext.nyc/search?q=kest

This write-up about the site is also fascinating: https://pudding.cool/2025/07/street-view/

Related. Others?

All Text in NYC - https://news.ycombinator.com/item?id=42367029 - Dec 2024 (4 comments)

All text in Brooklyn - https://news.ycombinator.com/item?id=41344245 - Aug 2024 (50 comments)

GitHub of the person who prepared the data. I am curious how much compute was needed for NY. I would love to do it for my metro but I suspect it is way beyond my budget.

https://github.com/yz3440

(The commenters below are right. It is the Maps API, not compute, that I should worry about. Using the free tier, it would have taken the author years to download all tiles. I wish I had their budget!)

I _love_ this but it's pretty bad. I searched for "Morgue" and one of the matches was the "2025 Google" watermark which it thought was "Big Morgue"

Again, a complex problem and I love it...

As others have mentioned, the idea is so cool, but the text recognition is abysmal.

Cool concept, but the accuracy seems quite low. The hits for "pedo" are pretty hilarious, though! https://www.alltext.nyc/search?q=pedo&p=2

This would probably make John Wilson's job a lot easier (https://en.wikipedia.org/wiki/How_To_with_John_Wilson)

520 matches on "hotdog" 8084 matches on "massage" in no particular order

I typed in "fart" and none of the results on the first page were actually the word "fart".

amazing. look up some graffiti writers you know

I immediately looked up "Blob Dylan"

Pretty cool

Searching for “foo” is humorous, it’s mostly restaurants with signs that say “food” but the “d” is cropped.

Search for “fart” if you want a good laugh.

This is exceedingly fun.

A game: find an English word with the fewest hits. (It must have at least one hit that is not an OCR error, but such errors do still count towards your score. Only spend a couple of minutes.) My best is "scintillating" : 3.

Gosh! Maybe one of these days someone will take time off from this cultural wonderment to construct a simple, easy to use, text-to-audio.file program - you know, install, paste in some text, convert, start-up a player - so that the blind can listen to texts that aren't recorded in audiobooks. Without a CS degree.

This is pretty cool! I'm curious what was used for OCR? Amazon Mechanical Burp?

There's a lot of PIZZA in New York City!

The creator gave a talk that has more details on how it was done: https://www.youtube.com/watch?v=gfODe92DzLU

IIRC he found a way to download streetview images without paying, and used the OCR built-in to macOS (which is really good).

This is a super cool project. But it would be 10x cooler if they had generated CLIP or some other embeddings for the images, so you could search for text but also do semantic vector search like "people fighting", "cats and dogs, "red tesla", "clown", "child playing with dog", etc.

I feel like street-view data is surprisingly underused for geospatial intelligence.

With current-gen multimodal LLMs, you could very easily query and plot things like "broken windows," "houses with front-yard fences," "double-parked cars," "faded lane markers," etc. that are difficult to generally derive from other sources.

For any reasonably-sized area, I'd guess the largest bottleneck is actually the Maps API cost vs the LLM inference. And ideally we'd have better GIS products for doing this sort of analysis smoothly.