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Osm2city.py

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Autogen Scenery
Started in 11/2013
Description Improved autogen support for FlightGear using OSM data
Contributor(s) radi, vanosten, Soitanen, portreekid
Status Under active development as of 02/2016
Topic branches:
$FG_SRC https://gitlab.com/osm2city/osm2city/
fgdata https://gitlab.com/osm2city/osm2city-data/
LOWI with OSM buildings

Take openstreetmap floorplans, create 3d buildings ready for use in FlightGear.

Development repository on gitorous. Forum thread osm2city.py development Written in python 2.7, developed on Linux. It should also run on Mac OSX. Windows users, see below.

It's at a rather early stage of development. There's no GUI, everything is controlled by an input file. But it produces realistic city layouts (after all, it uses realistic data). The whole process -- from scratch to flying in FG -- for a city the size of LOWI takes perhaps 30 min, including maybe a total of 15 min manual work.

It has been tested with Dresden, Germany (EDDC) and Innsbruck, Austria (LOWI). Both areas are now populated with about 50,000 buildings. Rendering this in FG is quite demanding. The FG process eats ~2.8GB RAM when flying in those areas, the download is ~50 MB each.

Status 06/2014

I'm currently adding textured roads, railroads, intersections and bridges.

Cquote1.png the shader is now on osm2city's git (in fgdata/). Again -- all credit goes to Emilian. He is improving the shader side, I will continue on the model side. So this is very much work in progress.

The shader requires the default renderer. No ALS/Rembrandt yet.

Get the LOWI roads pack (including the shader) here:
https://dl.dropboxusercontent.com/u/24846517/fg/osm2city/LOWI_roads.tar.gz

The fgdata/ folder goes to your $FGDATA.
In roads.xml enable either the lightmap or the traffic shader.
— radi (Fri Jun 13). Re: osm2city.py development.
(powered by Instant-Cquotes)
Cquote2.png
Cquote1.png Creating your own road network is a bit cumbersome ATM, I'll try to make it more general in the next few days. But if you're really, really keen on it:
  • get latest osm2city git
  • run roads.py -f your-parameters-file.
  • if you also create buildings, make sure to use the same BOUNDARY_* parameters for both osm2city.py and roads.py. Otherwise, buildings and roads might be misaligned. Basically, if your OSM file contains both roads and buildings, you can just use one parameters file.
  • roads.py will print an OBJECT_STATIC line, add this to your .stg
  • copy roads.ac to your scenery
  • copy roads.xml and tex/ from the LOWI roads pack to your scenery

— radi (Fri Jun 13). Re: osm2city.py development.
(powered by Instant-Cquotes)
Cquote2.png

Status 04/2014

Aerial view of LOWI, with 60k OSM buildings

Following Mathias' suggestion at FS Weekend 2013, I've now changed the code such that it merges all buildings per (osm2city) tile into one object, reducing the number of drawables from O(10k) to O(10). That indeed gives a nice speed-up. In fact, I'm overwhelmed by what's possible now -- here's a scene looking down at LOWI from FL300 showing 60k buildings. Plain Scenery 2.0 gives 19 fps on i7 Intel HD 5000 2560x1440. With buildings framerate goes down to 14.

Approaching LOWI, with 60k OSM buildings

The second scene, approaching LOWI from the east, went from 30 fps without buildings down to 20 fps.

Status 10/2013

Currently data is processed offline beforehand. Basically, it parses the OSM xml, generates a list of building outlines, discards some based on their area, simplifies the outlines, clusters them into ~500x500m blocks and different LODs, then writes .ac, .xml, and .stgs. OSM parsing is by far the most expensive, easily taking 10 minutes for 50k buildings. Once that's done, the remaining parts take maybe 1 minute in total. (Some optimization gave a huge speedup).

At the moment, the code knows only the floor plans. No streets, no runways, no land-use. But it'll certainly process such data in the future, and then could use some heuristics (some OSM buildings are labeled "Terminal 1" or so) to apply terminal/hangar textures to buildings at airports. This way we could rather easily populate some airports with 'semi-generic' terminal/hangar buildings.

Features

  • reads buildings from OSM. Honors height and level tags, reads relations ('buildings with holes')
  • reads existing .stg, won't place OSM building if there's a static model nearby
  • reads pre-calculated terrain elevation: places buildings at correct elevation
  • simplify/automate elevation probing by using fgelev
  • LOD animation based on building height and area (see below)
  • cluster a number of buildings into a single .ac files. Clusters overlap to alleviate sharp LOD borders
  • complex sloped roof generation (using Olivier Teboul's implementation of the straight skeleton algorithm)
  • texture manager: DB of facade/roof textures
  • ~10 different, hi-res facade textures, some roof textures
  • find matching texture for given building (number of levels, modern/old building, etc)
  • find matching roof texture for given facade texture
  • basic lightmap support (currently broken)
  • obstruction lights on tall buildings
  • command line interface and parameters file (thanks to forum user vanosten)
  • shows statistics on processed buildings
  • writes .ac, .xml, .stg

Planned Features

(in random order)

  • more complex facade generation. Currently, all sides get same texture Not done Not done
  • Rembrandt lighting Not done Not done
  • put a piece of matching ground texture around buildings ('garden') 10}% completed
  • put shared models if/where OSM indicates so: gas stations... Not done Not done
  • geometry cleanup, simplify too complex buildings Done Done
  • use residential/industrial/commercial tags/areas. ATM, all is residential. Not done Not done
  • geometry cleanup, simplify too complex buildings Done Done
  • Batch processing of greater areas including downloads (PortreeKid)
  • use more LOD levels, write them to different .ac so users can easily reduce building density, therefore improve performance 50}% completed
  • put large buildings into one ac, sort/rate buildings by stand-out-ness Done Done
  • then ship light/med/full .stg Not done Not done
  • mid-term: develop this into a city-engine that procedurally generates a city based on OSM roads. Not done Not done
  • read, drape, texture roads and railways 70}% completed
  • texture road intersections Not done Not done
  • illuminate roads Not done Not done
  • procedural bridges 30}% completed
  • place shared models along roads if no OSM data available Not done Not done
  • long-term: integrate into FG to do all this on the fly. Not done Not done

LOD Scheme

FlightGear knows three standard LOD: bare, rough and detail. 'Bare' sets the drawing distance of the terrain, which may easily be 50 km or more. Drawing buildings 50 km out makes little sense (unless they are really tall), so we shouldn't use this level here. Of the remaining two standard levels, 'rough' is used for large and/or tall buildings, and 'detail' for smaller ones.

Osm2city can generate complex roof shapes. This increases the poly count further, and I believe it's a good idea to use another LOD 'roof' for complex roofs. Fortunately, we can change every aspect of FlightGear, and adding another LOD is easy. Use the FG command line

--prop:double:/sim/rendering/static-lod/roof=2000

to set the distance for 'roof' to 2 km. If you want to adjust it via FG's GUI, copy static-lod.xml (from osm2city's git repo) to $FGDATA/gui/dialogs.

Ideas

  • nearby hi-rise objects of similar shape get same texture? Probably too special a feature.
  • bump map/reflection effects?
  • a mode that generally uses shared models? If we find a shared models of matching floorplan, use this instead of creating a new, individual building? Will break clusters.
  • a terrasync-like thing? Users get OSM buildings

(where available) on-the-fly? Might be quite costly in terms of runtime performance and bandwidth. The OSM download (buildings only!) is ~40MB for the 25x25km LOWI area.

Install

  • dependencies: Install the following packages (names from Debian packages):
 python-numpy python-shapely python-matplotlib python-scipy python-pil
  • get osm2city from gitorious
  • add the directory with osm2city modules to your PYTHONPATH (unless your PYTHONPATH already contains . (the dot))
  • get the textures as described in the first post of the devel thread. Put the folders into your osm2city folder.
  • copy elev.nas to $FGDATA/Nasal/
  • Change the in variable of elev.nas to match the elev.in file e.g. $FG_DATA/Nasal/evel.in
  • Change the out variable of elev.nas to the export directory with a filename

with write access (e.g. $FG_HOME/Export). See IORules and $FG_HOME

Install on Windows

osm2city is pure python. Install the following packages.

http://www.lfd.uci.edu/~gohlke/pythonlibs/#numpy

http://www.lfd.uci.edu/~gohlke/pythonlibs/#shapely

http://www.lfd.uci.edu/~gohlke/pythonlibs/#scipy-stack

TODO: PIL or pillow

Workflow

There are five main steps:

  • get OSM data
  • adjust input file
  • create elevation grid, run FG to probe elevation data
  • run osm2city
  • install the generated scenery

We'll now walk through these steps in detail:

get OSM data

  • decide on a region you want to populate. Get its lon/lat coordinates.
  • create a project directory. We will use LOWI/ in this example.
  • get corresponding OSM data in its native .xml format.

There are several options to get OSM data. You may find the XAPI Query Builder helpful, it will generate a download URL that you can fetch with wget:

wget -O buildings.osm http://www.overpass-api.de/api/xapi?map?bbox=11.16898,47.20837,11.79108,47.38161

Put this data into LOWI/buildings.osm

Adjust input file

  • Now adjust the input file. Copy the template params.ini to LOWI/. Edit this file, adjusting (at least) the following (check comments in params.ini):
  • PREFIX = LOWI (the project directory)
  • BOUNDARY_EAST, BOUNDARY_NORTH, BOUNDARY_SOUTH, BOUNDARY_WEST
  • OSM_FILE = buildings.osm
  • set PATH_TO_SCENERY to a standard FG_SCENERY path. Suppose the area you want to populate is /home/user/fgfs/scenery/Objects/e010n40/e011n47/, PATH_TO_SCENERY would then be /home/user/fgfs/scenery/ .
  • you might want to set MAX_OBJECTS to a small number (say, 100) for your first try. This will limit the number of buildings parsed, and speed up the whole process.

Probe elevation

  • probe elevation for the region in params.ini:
  • Set the ELEV_MODE in params.ini
  • ELEV_MODE = Manual
  • run tools.py (tools.py -f LOWI/params.ini), this will create a file elev.in. Copy elev.in to $FGDATA/Nasal/
  • tools.py will tell you to hide a certain scenery/Objects/... folder, to prevent probing elevation on top of existing objects. Simply rename the folder
  • run FG, open debug->nasal console, enter: elev.get_elevation(), press execute. Might take a long time, depending on the area scanned. This will write elevation data to /tmp/elev.out (which is actually just plain 5 column data: lon,lat,x,y,elevation). Put elev.out into LOWI/
  • unhide, rename the objects folder
  • ELEV_MODE = Telnet
  • Run setup.py
  • Start FG with the properties service on Port 5501
  • Run tools.py, this will create a elev.in, start the nasal script and copy the elev.out back to your project directory
  • ELEV_MODE = Fgelev
  • Set FG_ELEV to your fgelev executable
  • Set PATH_TO_SCENERY (Missing terrain will result in error message)
  • Run tools.py this will generate the elev.out using fgelev This can take considerable time.

Run osm2city

  • run osm2city.py -f LOWI/prams.ini. Parsing OSM data again takes quite looong (10 minutes or more for 50k buildings) is now pretty fast, but the result is cached to file buildings.pkl. Next startup will be much faster if you move buildings.pkl to LOWI/buildings.pkl and even faster if you set USE_PKL = 1.

If all goes well, files like LOWIcity0101.ac and their corresponding .xml, along with .stg files, were created and moved to the correct location in $FG_SCENERY

  • copy the tex/ folder into the objects folder where these files were created

Improve frame rate

  • adjust LOD ranges in FG
  • decrease MAX_OBJECTS, increase LOD_*

(- use larger/smaller tiles? Tradeoff between distance calculations/xml parsing and GPU)

Contributing

You know some python? Or you're keen on writing docs? Or just want to use osm2city, but got stuck somewhere? Contact radi on the FG forum. None of the above? Take pictures of buildings where you live! I'm especially interested in south-east asian style architecture, as I'm planning to populate Hong Kong Kai Tak (VHXX) in the future.

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