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Code needed for building the data and learner for predicting chiptunes using
MIDI representations
Files
data/
raw/*
- All of the MIDI files that have been generated and collected so
far
all_songs/*
- A subset of the *raw* directory that only includes songs that
have been manually labeled as "songs", as opposed to empty
tracks, sound effects or other background songs.
training_songs/*
- A subset of the *all_songs* directory, approx 2/3 of it,
containing songs that should be used to generate and train
the algorithm with.
testing_songs/*
- A subset of the *all_songs* directory, containing the approx
1/3 of the songs that are not in the *training_songs* directory,
that should be used for testing the accuracy of the algorithm
training_counts.sqlite3
- The generated sqlite3 database of transition counts (generated
with the *training.py* file) based off the *training_songs*
directory
Installing
install python-midi by running:
cd contrib/python-midi
python setup.py install
install MIDIUtil by running:
cd contrib/MIDIUtil
python setup.py install
You'll also want to generate some training counts. You can do so with:
python training.py
Related Software
nes2midi
Windows tool for converting NSF files to MIDI. The original software is in Japanese, but there is thankfully an English translation too!
WINE
Windows DLL implementation used for running the above software on OSX and Linux. OSX instructions are available on the WINE site.
About
Code needed for building the data and learner for predicting chiptunes using MIDI representations