
DeepOSM: Detect roads and features in imagery with neural nets using OpenStreetMap - chippy
https://github.com/trailbehind/DeepOSM
======
therobot24
oddly enough a relevant arXiv paper was released today:
[https://arxiv.org/abs/1605.08323](https://arxiv.org/abs/1605.08323)

Also how does it compare with [https://github.com/mitmul/ssai-
cnn](https://github.com/mitmul/ssai-cnn)

~~~
andrewljohnson
Great find, I'll add that to the references on DeepOSM.

Looking at that repo, the main differences are:

* that code applies to a specific (massachusetts) data set, while DeepOSM uses nationwide USA NAIPs trained against OSM extracts

* they seem to have implemented the full Mnih CNN - DeepOSM just uses a single layer as is

* Mnih didn't touch on using the infrared band

In general, that project seems more mature in replicating Mnih than DeepOSM.
Our next goal is a website to show errors in OSM data to be corrected, rather
than finish making the net deeper.

edit: added links to paper and code
[https://github.com/trailbehind/DeepOSM/commit/8053057635a1a0...](https://github.com/trailbehind/DeepOSM/commit/8053057635a1a066ef5aecc8f70b6e2b0c7115d6)

~~~
ZeroGravitas
When you say:

> Our next goal is a website to show errors in OSM data to be corrected

Do you mean feeding the data to one of the existing projects that crowdsource
fixes based on lists of potential errors, or a new custom site?

~~~
andrewljohnson
Custom site to start at least, I don't consider any of this really production
ready yet.

Here's the app work:
[https://github.com/trailbehind/DeepOSM/compare/feature/deepo...](https://github.com/trailbehind/DeepOSM/compare/feature/deeposm.org?expand=1)

~~~
ZeroGravitas
It might be worth considering integrating with

[https://github.com/osmlab/to-fix](https://github.com/osmlab/to-fix)

or

[https://github.com/maproulette/maproulette2/](https://github.com/maproulette/maproulette2/)

to help with evaluating/fixing of the errors you find.

------
MichailP
Offtopic, but does someone know a good reference and explanation for OSM tags?
A lot of meaning is derived from tags, since the underlaying data structure is
just nodes, ways and relations. And since the data is crowd sourced use of
tags could be inconsistent, data could overlap and repeat itself. How someone
makes a complex project like [1] using data like this?

[1] [http://project-osrm.org/](http://project-osrm.org/)

~~~
skyebook
Taginfo[1] provides statistics on tags in use and there's a huge amount of
documentation for tags (differences between tags, how to use them in certain
situations, etc) in the wiki.

As an example, the page for highway tags[2] is quite rich.

[1] [https://taginfo.openstreetmap.org](https://taginfo.openstreetmap.org) [2]
[http://wiki.openstreetmap.org/wiki/Key:highway](http://wiki.openstreetmap.org/wiki/Key:highway)

------
mietek
The author mentions difficulties with locating the full text of some papers.
This seems like a good time to point out that you can take some DOI URLs, such
as
[http://dx.doi.org/10.1145/2424321.2424336](http://dx.doi.org/10.1145/2424321.2424336)
, and turn them into freely-accessible DOAI URLs, such as
[http://doai.io/10.1145/2424321.2424336](http://doai.io/10.1145/2424321.2424336)
.

Also, see [https://www.reddit.com/r/scholar](https://www.reddit.com/r/scholar)
.

------
rburhum
Clearly this is super cool. It is also a legal licensing nightmare since it
takes "derived product" to a new level...

~~~
dublinben
The license of the OSM database allows for derivative works as long as they
are under the same copyleft license. No nightmare at all.

~~~
rburhum
The nightmare comes when you mix it with proprietary datasets that you license
from somebody else. Many companies right now are doing that and it is dubious
grounds to stand on.

