How to find a street in 2 minutes [video]

https://www.youtube.com/watch?v=rl2Q9xH8e7M

by gofiggy • 3 years ago

263 65 3 years ago

sturza• 3 years ago

Cannot generalize outside the US

HenryBemis• 3 years ago

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).

newaccount74• 3 years ago

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)

sellyme4• 3 years ago

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 majority of cases.

pvitz• 3 years ago

Not exactly US-specific, but Streetview isn't available everywhere. How would he have found the exact location without it? Would be quite interesting!

Adverblessly• 3 years ago

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?

Kiro• 3 years ago

You clearly don't know who Rainbolt is. He can do this anywhere in the world.

ape4• 3 years ago

Besides doing the OSM query his "method" is also being really observant and resourceful

Mordisquitos• 3 years ago

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/

Morizero• 3 years ago

It's a surprising helpful tool in Pokemon Go metagaming. For example, you can use it to determine gyms eligible for EX Raid status (not that that's a thing anymore), find potential micro-nests, or even locate Lake Trio spawn locations.

dav_Oz• 3 years ago

Basically, that is the gist of the vid, the rest is more or less common sense, I guess.

A short & catchy variation of "Overpass turbo - a super powerful mining tool for OSM" would be a more appropriate title [0][1]. It exists since 2013 but got a massive boost from the Pokémon Go craze in 2016 [2].

[0]https://wiki.openstreetmap.org/wiki/Overpass_turbo

[1]https://wiki.openstreetmap.org/wiki/Overpass_API

[2]https://www.itechpost.com/articles/34612/20160930/pokemon-go...

wfleming• 3 years ago

And in this case I think it would have been a lot of work to identify the number plate & bin logo if he hadn’t already had enough context to make a probable guess. The source image he was working from looked pretty low-res, that license plate was just a couple white-ish pixels. Like you, I hadn’t heard of overpass turbo and that looks super cool, but the rest of it was “how to confirm what you already mostly know”.

shlubbert• 3 years ago

How dare someone mention some common sense tips as a tiny part of a video. Shameful!

iandanforth• 3 years ago

Also I would not have assumed that ChatGPT could generate code for such a niche tool, so that was useful as well.

capableweb• 3 years ago

I mean, it's probably niche if you consider all software ever, but the tool has been around since 2013 at least (and before that under a different name, OSM Server Side Scripting/OSM3S), with a lot of ecosystem tools and documentation (in multiple languages) existing all over the place, I wouldn't say it's very niche in the mapping community.

pests• 3 years ago

This comment has no valuable take.

jader201• 3 years ago

I think it does: It saves watching the video by providing a link to a tool that he mentions that many might not have heard of.

dclowd9901• 3 years ago

One of these I had seen had almost no hints, but it did have a church that was fairly close to a kfc and a dollar general or something. It also kind of “looked” like the southeast, so the dude did a general query on places where those three types of structures inhabited the same general area. It came back with about 7 or 8 results in the entire southeast which could then be manually checked so it seemed like being able to query the map did the big lifting there.

ragebol• 3 years ago

I'm thinking of a new game: write the shortest Overpass Turbo query that yields, say, 1 result for eg. your country.

Aachen• 3 years ago

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)

Tempest1981• 3 years ago

There's a transcript here, but not very readable:

https://youtubetranscript.com/?v=rl2Q9xH8e7M

resoluteteeth• 3 years ago

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

DANmode• 3 years ago

s/frequently/occasionally

Years of use, rarely isn't perfect condition.

MontyCarloHall2• 3 years ago

I wonder how hard it would be to develop/train a machine learning method that ingests a photo of anywhere outside and maps it to corresponding satellite/aerial imagery.

We are of course very good at object recognition from still images. We are reasonably good at inferring depth from a single still image (monocular depth estimation [0-2]).

Combining these, we should be reasonably good at determining relative positioning of identified objects in 3D, and thus computing their overhead 2D positions. Imagine discretizing overhead x/y positions, essentially yielding an image where each pixel corresponds to a 1 meter square looking down, whose color is the inferred identity of what occupies it.

For example, in the linked album cover, we could infer that a street occupies a set of pixels with coordinates S = {(x1, y1),...(xN, yN)}; a building occupies pixel set B1 = {(xb1, yb1),...(xbM, ybM)}; another building pixel set B2; etc.

Now, we are also reasonably good at object recognition (and MDE) for overhead imagery [3]. This would let us build a giant set of overhead object identities inferred from the entirety of satellite imagery. The tricky part would be efficiently indexing this, such that the overhead coordinate sets inferred from the ground-level image could be quickly (and fuzzily) queried in the satellite data. A brute-force approach would essentially convolve the overhead object coordinates inferred from the ground-level image over every region of the satellite imagery, at every possible angular orientation (and likely several different scales, since MDE is often imperfect at inferring absolute depth), but this would be impractically slow.

I would bet that intelligence agencies have had this capability for some time now.

[0] https://www.sciencedirect.com/science/article/pii/S095070512...

[1] https://www.nature.com/articles/s41598-022-20909-x

[2] https://keras.io/examples/vision/depth_estimation/

[3] https://www.mdpi.com/2072-4292/12/17/2719

apocalyptic0n3• 3 years ago

There was an article about that on HN in the last few weeks. I struggled to find that specific post, but I think this is the same story. https://www.theregister.com/2023/07/15/pigeon_model_geolocat...

MontyCarloHall2• 3 years ago

The model [uses] semantic geocells – bounded areas of land, similar to counties or provinces, that consider region-specific details like road markings, infrastructure quality, and street signs
The model can['t] pinpoint exactly where a street-level photo was taken; it can instead reliably figure out the country, and make a good guess, within 15 miles of the correct location, a lot of the time

I could imagine that a more qualitative model like this one could be used to restrict the search space of a more quantitative model akin to the one I (very roughly) proposed.

egman_ekki• 3 years ago

I think Google Maps is doing something similar where it sometimes asks you to take photos/a video of the street you’re walking on to detrmine your location more precisely (I think it happens when the GPS is not giving good enough precision).

praptak• 3 years ago

There's a separate augmented reality mode which a) captures frames in real time to pinpoint your position and b) displays the video stream with overlaid 3D markings which show you the way.

Drew_• 3 years ago

I _think_ this is more to do with calibrating the compass than precise location

operator-name2• 3 years ago

You may be interested in a lesser scoped project that Rainbolt played against: https://youtu.be/ts5lPDV--cU

TylerGlaiel• 3 years ago

note that when they went and analyzed that AI they found out it was using the smudges on the google car camera as a sort of fingerprint (as those are consistent for the many pictures taken by one camera) so that AI would almost certainly not do well against pictures taken from different sources

mavili• 3 years ago

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.

raldi2• 3 years ago

I think one of the lessons here is how many kinds of clues like that there are, once you know what to look for.

tekla• 3 years ago

Knowing things is part of skill.

josefx• 3 years ago

The main clue is knowing that Jack Harlow is from Louisville Kentucky, so he is basically guessing that the picture was also taken there and just confirming it by checking if the license plates and logos match those he can find for that area.

silisili• 3 years ago

I wish he'd have done a harder one. This one felt too easy, because you can just Google where he's from, and just Google search '1948 address louisville ky'.

sellyme4• 3 years ago

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.

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.

raldi2• 3 years ago

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.

netsharc2• 3 years ago

Switzerland has a different electrical outlet to the rest of Europe (Type J), and an easy way to spot fake apartment listings is when the pictures of the apparent apartment show "EU" outlets (Type F).

https://www.worldstandards.eu/electricity/plugs-and-sockets/

teddyh• 3 years ago

I prefer this link: <https://en.wikipedia.org/wiki/AC_power_plugs_and_sockets>, since it gives more information, especially the proper names for the connectors, not just the IEC type code. If you want a more official list, use this one: <https://www.iec.ch/world-plugs>.

alexdeloy• 3 years ago

Rainbolt is an amazing geodetective without doubt.

There was also a great talk about Overpass Turbo and related OSINT tools on the 2021 CCC Congress, also showing examples outside the US.

The talk is available in english as well: https://media.ccc.de/v/rc3-2021-r3s-112-osint-ich-wei-wo-dei...

kylecazar• 3 years ago

Anyone interested in this should check out GeoGuessr. Fun way to kill some time.

kasperni• 3 years ago

If you a new to GeoGuessr this is probably a more interesting video from the author [1].

[1] https://www.youtube.com/watch?v=0p5Eb4OSZCs

ThisIsMyAltFace• 3 years ago

I always wonder if any of the US intel agencies have reached out to Rainbolt for consulting or recruitment.

Giorgi• 3 years ago

I bet that's his passive income

sharkweek• 3 years ago

It’s a meme now on his channel that he works for the CIA given his recent travels et al.

He made a funny video about taking the “test” on the CIA’s website which was an online game for kids (a really weird thing to exist when I stop and think about it).

https://youtu.be/8aanIIDgm5Q

jrochkind1• 3 years ago

overpass turbo is a tool I didn't know about, which does some of the heavy lifting here -- and could do even more in other cases, his example of "skate park within 100 meters of a dog park" makes me think. i didn't actually realize there were public databases available with that kind of granularity, coverage, and coding.

The ability to have ChatGTP generate the query is actually pretty huge.

I wonder how long until there are AI tools where you can just say things like "give me skate parks within 100 meters of dog parks in Boulder CO", and it will identify the tool to use and generate the query and execute the query and just give you the answers.

leokennis• 3 years ago

That public database is Open Street Maps which I’d describe as “Wikipedia for map data”.

It’s amazing plus it’s probably used in several tools/apps/services you use regularly.

And best of all, if you have a look at the map around someplace you’re familiar with there are probably several improvements and additions you can make this very day using their online map editor.

renewiltord• 3 years ago

Haha he's a pretty entertaining guy. Good tip on Overpass Turbo. It's wild that open data is full of so much stuff and enables all these use cases. Big fan of the tool as well.

jokoon3• 3 years ago

Well, this was the easy version, since there were a lot of clues.

I really think those tools should be banned, they're such an immense security problem.

I know those can be useful, and I understand that information should be free, but they can still do quite a good amount of harm.

Lesson: ALWAYS blur anything that could identify a street or anything when you post a picture online.

wds• 3 years ago

The tool is banned.

Legitimate users no longer have access to it, Bad actors continue to use the software on their own hardware anyways.

63• 3 years ago

But the barrier to entry to being an effective bad actor is much higher, and some harm is prevented even if not all.

I think your point is valid to consider but it uncharitably overlooks the positives of the other side's proposition and reduces it down to all or nothing.

brmgb2• 3 years ago

Genuine question, what exactly is the security problem here?

It’s a set of basic techniques to find where a photo was taken. I have a hard time envisioning an actual new issue here.

Obviously, people shouldn’t post pictures of things they don’t want other people to see or know (like where you live if you don’t want people to know that) but that was already true before people could easily mine Openstreet map data.

jokoon3• 3 years ago

Overpass is not just "mining OSM data", overpass is quite an extremely efficient language and system plugged to a GIS database, that can be used to find a lot of things.

Those things could be used by robbers or any other kind of people who browse photos online.

Now, of course it depends on people handling their data straight, but since the internet is mostly used as a place where people share anything to the public, I still believe it's a bad combination of problems waiting to happen.

operator-name2• 3 years ago

Is it not the data that is the problem rather than the tool?

mk_stjames• 3 years ago

I think the real discussion here should be an analysis of his methods of using the various online tools... his toolchain, essentially, and how we're rapidly accelerating processes like these compared to even just 10 years ago.

Openstreetmap data is used in Overpass Turbo -> ask ChatGPT NLP into Overpass Turbo scripted API -> copy paste script into Overpass Turbo -> select Location data from query -> copy/paste coords into Google Street View images -> Matching the original image by eye.

This part of the his search could be collapsed into a single tool. Or, if that is maybe too much of a specific use case, imagine moreso a 'workbench' tool that would put all this in a single place. Every time he switches chrome tabs, or copy/pastes... that could be taking place in a single environment, like a GPT4-plugin for example.

scanny• 3 years ago

This seems to cover some of that workflow

https://github.com/rowheat02/osm-gpt

qalter• 3 years ago

I have a lot of old pictures without geolocation data. A tool to automatically add even an estimate of the location would be really useful so that apple or google photos could use it to make albums automatically.

PIGEON is going that way I guess: https://arxiv.org/abs/2307.05845

How to find a street in 2 minutes [video]

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