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Tokenize MIDI files for neural network processing

Project description

Midi Neural Processor (Fork)

This repository is a fork of this repo with the main objective of structuring as an installable python package via pip.

  • Repository for midi-based machine learning model's {pre/post} processing.

  • You can use this processor in any machine learnig library like tensorflow, pytorch, etc...

  • This processor's algorithm is based on PerformanceRNN & Music Transformer (Polyphonic Music) Model's preprocessing algorithm suggested by Google Magenta.

Simple Usage

Install

$ pip install midi-neural-processor

Encoding & Load midi file

  • You can load & encode your midi file just one line
  • encode_midi() is a role of pre-processing.
from midi_neural_processor.processor import encode_midi
encoded = encode_midi('bin/ADIG04.mid') ## 'bin/AIDG04.mid' is midi file path.
## output: [int, int, int, int, ... ].
## int range is range(0,388). 388 = NOTE_ON + NOTE_OFF + TIME_SHIFT + VELOCITY 

Decoding

  • decode_midi is convert integer array to midi form.
  • you can gave method to file_path as a second args in that if you want to save midi as .mid file.
  • all elements in integer array should be range(0,388).
from midi_neural_processor.processor import decode_midi
decode_midi(encoded, 'bin/test.mid') ## 'bin/test.mid' is midi file path.

Comming Soon

  1. Pedal Control
  2. Midi Converter to .tfrecords

License

Project is published under the MIT licence. Feel free to clone and modify repo as you want, but don't forget to add reference to authors :)

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