Hackathon entry for NASA Space Apps 2018. http://songsat.ca
Converts image data to music given the theme.
This is NOT the website. This is the code that powers the music played on the website. To see the source code for the https://songsat.ca and how to modify it for your own use, head over to my repository here: http://github.com/mcvittal/mcvittal.github.io
Spatial manipulation dependencies:
gdal, pyproj, osr
Image manipulation:
matplotlib, PIL, numpy
MIDI:
midiutil
Preinstalled system libraries:
subprocess, os, random
Currently, it uses one of GDAL's standalone programs, gdallocationinfo to be installed and in the users path. This will change in V2 (See next section "A note to users")
This project currently requires two very large TIF files for the automatic land cover detection - one of mountain ranges supplied by the UNEP, and the other of a global land use dataset created by NASA from MODIS imagery. They are too large to host on Github uncompressed, and as such are stored in a tarball and need to be decompressed, and left in the same folder as the getclass shell script. They are just under 20gb uncompressed, so be sure you have enough disk space before decompressing. A V2 of this project will involve them being hosted on a cloud provider and having a REST API returning the values currently being generated locally.
To use this, simply invoke the songSAT method and provide a path to a GeoTIFF (Ideally, landsat or a clipped landsat image). It will attempt to assess the geographic contents of the image by getting the center coordinates, and finding what land cover is there using the getclass shell script. If a supported land type is discovered, it will then pass that information along with the data to the generate_song method, and produce a MIDI file (by default /tmp/OUT.mid). Simply open the MIDI file in your media player of choice, or in your notation software of choice to listen!