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Cezary Pukownik 7d5cd31bdd new library for midi processing
2019-07-03 13:09:49 +02:00
..
__pycache__ -init-first-stage- 2019-05-28 12:40:26 +02:00
data add readme 2019-06-19 10:53:44 +02:00
generate.py LSTM Music Generator 2019-06-19 15:48:39 +02:00
midi_processing.py new library for midi processing 2019-07-03 13:09:49 +02:00
midi.py LSTM Music Generator 2019-06-19 15:48:39 +02:00
readme.md readme.md 2019-06-19 17:49:28 +02:00
settings.py data extraction to groups of instruments; drums is now avaible 2019-05-30 23:11:25 +02:00
settings.pyc -init-first-stage- 2019-05-28 12:40:26 +02:00
train.py LSTM Music Generator 2019-06-19 15:48:39 +02:00

readme.md

MUSIC GENERATION USING DEEP LEARNING

AUTHOR: CEZARY PUKOWNIK

Files:

  • midi.py - code for data extraction, and midi convertion
  • train.py - code for model definition, and training session
  • generate.py - code for model loading, predicting ang saving to midi_dir
  • settings.py - file where deafult settings are stored
  • readme.md - this file

Directories:

  • data/midi - directory where input midi are stored
  • data/models - directory where trained models are stored
  • data/output - directory where generated music is stored
  • data/samples - directory where extracted data from midi is stored
  • data/samples.npz - deprecated

How to use:

  1. Use midi.py to export data from midi files

./midi.py [midi_folder_path] [output_path]

  1. Use train.py to train a model (this can take a while)

./train.py [input_training_data] [model_save_path] [epochs]

  1. Use generate.py to generate music from trained models

./generate.py [trained_model_path] [output_path] [treshold]