25 points by dfworks 2 days ago
Inspired by All Text in NYC (https://alltext.nyc) by Yufeng Zhang I thought I would replicate something similar for London.
A searchable tool that lets you explore text captured across Google Street View imagery in London; shop signs, posters, graffiti, van numbers etc
Related:
Search all text in New York City - https://news.ycombinator.com/item?id=44883304 - Aug 2025 (116 comments)
All text in Brooklyn - https://news.ycombinator.com/item?id=41344245 - Aug 2024 (50 comments)
Hi Author here,
This doesnt really answer your question but hopefully gives some insight into our process.
The main bottlenecks were breaking the fisheye-style panoramas into different perspectives (so text was more readable), passing it to OCR and acquiring the panoramas as there isn't an official API.
Because of the above, we constrained ourselves from the outset. For example, the spacings between panoramas was 50m, we didnt traverse residential roads that were less likely to have signage, we only used the most recent panorama for a location etc
If I interpret global as without those constraints (5m spacings, every road, all historic panoramas) then I think the first problem you'll run into is being rate limited by Google. Compute may be able to solve the other problems but it would be very expensive.
After inputting a text from my phone, I just get a:
Subscribe to Public Insights for just £29/month More data. Better value.
When I search "Colliers Wood", with or without quotation marks, each results match only one of the words.
There are around 50 results for Crystal Palace, Ill have a look through the logs to see what might have gone wrong
Sadly no R Soles though (A shoe shop formerly in Chelsea but now online) - however, just searching for profanities does bring back some graffiti
For [batman] it only finds this one poster,
https://maps.app.goo.gl/jmJ1qhQsB3AetLiK8
But doesn't find this billboard, probably because it doesn't actually contain the text "Batman".
https://maps.app.goo.gl/nBoHArvaKZSgRH5W7
It should be able to match text query to anything, not just text.