No, it is not included, however there must be quite a lot of pictures on internet for most cities.. Geoguesser data is same as Google's street view data and it probably contains billions of 360 degree photos.
It just isn't plausible that anyone has actually done that. I'm sure some people include a small sample of them, though.
Why bother to create a copy, if it can be avoided, right?
This is a good rebuttal when someone quips that we “are about to run out of data”. There’s oh so much more, just not in the form of books and blogs.
This is not uncommon. Bears aren't always tearing people apart, that's a movie trope with little connection to reality. Black bears in particular are smart and social enough to befriend their food sources.
But a hungry bear, or a bear with cubs, that's a different story. Even then bears may surprise you. Once in Alaska, a mama bear got me to babysit her cubs while she went fishing -- link: https://arachnoid.com/alaska2018/bears.html .
They still kicked ass.
It seems like those AIs just have an awful lot of location familiarity. They've seen enough tagged photos to be able to pick up on the patterns, and generalize that to kicking ass at GeoGuessr.
I'm fairly certain this phenomenon is responsible for LLM capabilities on GeoGuesser type games. They have unreasonably good performance. For example, being able to identify obscure locations from featureless/foggy pictures of a bench. GeoGuesser's entire dataset, including GPS metadata, is definitely included in all of the frontier model training datasets - so it should be unsurprising that they have excellent performance in that domain.