31–40 of 69 posts
I once saw a Johnny Long talk about how to do this for interior photos, where something like an electrical outlet or carton of milk can make all the difference in the world.
https://www.worldstandards.eu/electricity/plugs-and-sockets/
Checking on numberplates and bin logos was hardly groundbreaking, as those are exactly where I would have started too. However, I had never heard of Overpass Turbo [0]. Learning of its existence was the only valuable take from this video for me, but well worth it. [0] https://overpass-turbo.eu/
Earlier quoted context omitted.
I haven't used his method (or tools) for finding locations. On his video though he does mention Austria/Vienna for museums, etc (on his screenshare), so I assume (assumption1) that if it shares data with OsmAnd (and others) it would be very useful for (anywhere) where internet is prevalent (Americas, Europe, Oceania, most of Asia).
The data is from Open Street Maps. Their data is world wide, but quality of coverage varies wildly. Austria for example has very good maps in OSM, South Korea on the other hand has much lower quality maps (probably fewer people there using OSM)
https://jsis.washington.edu/news/south-korean-data-localizat...
> The purpose of the Korean Land Survey Act was to prevent anyone who is threat to national security from stealing the country’s maps during the post-war period. ROK government enacted the law in 1961 and it concerned the establishment and management of spatial data — it has subsequently been amended in 2009. The Article 16 of the act states strict regulation on taking maps, photos, the results of a survey, or any land surveillance data abroad, because of the likelihood that it could harm South Korean national security interests.
Getting http 403 errors in NewPipe after the first minute of watching. After twitter and reddit, I guess it's time to wall another garden :( wish people would at least cross-post information to literally any other website (so there's a semblance of market forces—reasons to be nicer to use than the competition—and not just 1 place you have to use)
For their entire existence, newpipe and youtube-dl/yt-dlp have frequently stopped working and needed to be updated to deal with changes in youtube. This is nothing new; youtube was never open. It's also not as if most other video sites provide an open api that doesn't need to be scraped
Years of use, rarely isn't perfect condition.
Earlier quoted context omitted.
I genuinely can't work out what part of this video you think is US-specific. America is far from the only country in the world that has municipality logos on infrastructure, house numbers, or OSM coverage. There's certainly regions of the world where doing this would be much more challenging (e.g., Central Africa, China, rural India), but the stuff he covered in the video is going to be extremely helpful in the vast…
Not exactly US-specific, but Streetview isn't available everywhere. How would he have found the exact location without it? Would be quite interesting!
Earlier quoted context omitted.
I genuinely can't work out what part of this video you think is US-specific. America is far from the only country in the world that has municipality logos on infrastructure, house numbers, or OSM coverage. There's certainly regions of the world where doing this would be much more challenging (e.g., Central Africa, China, rural India), but the stuff he covered in the video is going to be extremely helpful in the vast…
One thing I noticed that doesn't generalize is exactly those house numbers. Depending on house numbering scheme, a house number may effectively be useless. Here in Israel house numbers are just sequential and most streets aren't that long, so what are you going to do with a number like "17" which appears in almost every street in the country?
Exactly the same thing that Rainbolt did in this video: cut down the amount of work you have to do on each street from checking dozens or potentially hundreds of photos/angles to just 1-3.
Of course if you've only narrowed the streets down to 20,000 candidates instead of 20 of them, that doesn't get you straight to the answer, but it's still a massive proportional improvement.
But the lesson being presented here is to use data that's available to you in the photograph. Maybe you don't have any street numbers (or any particularly useful ones) visible, but you can see the sun at the end of the road and therefore know that it's running directly East-West. That filters out tons of roads. Maybe you can see that houses are only on one side and a river is on the other, you can use that as well. In the video he mentions similar constraints with regards to local parks as being other options for this kind of search narrowing.
The point of that portion of the video isn't "hope the house number is really weird lmao", but to extract any geographical information out of the image and then query that with open mapping databases. House numbers are just one of the most common ones, and while they're typically not quite as powerful as was shown in this video, they're very often going to help dramatically.
Maybe this is common knowledge in the US, but like, you're just supposed to know what Kentucky number plates look like from a blurry image, and you're also supposed to know the logo of a sports club? Cool. Also, picture has to contain all these clues of course, conveniently, including a couple of street numbers.
Knowing exactly what they look like would help, but the point is more that you're supposed to look them up and see if they match to rule out regions or confirm suspicions. You've got the wealth of human knowledge at your fingertips, use it - if knowing what a Kentucky numberplate looks like might be useful, you can just look that up in a matter of seconds.
> Also, picture has to contain all these clues of course, conveniently, including a couple of street numbers.
Given how many times this individual has narrowed down an exact location from a photo of a straight road with nothing but trees on either side, I think it's fair to suggest that he was picking an easy target for the purposes of tutorialisation.
It might take more than a couple of minutes to narrow down a photo with less obvious clues than this one, but it's fairly difficult to take a photograph outdoors that doesn't give away enough for someone with sufficient knowledge to identify exactly where it was taken.
Checking on numberplates and bin logos was hardly groundbreaking, as those are exactly where I would have started too. However, I had never heard of Overpass Turbo [0]. Learning of its existence was the only valuable take from this video for me, but well worth it. [0] https://overpass-turbo.eu/