praca-magisterska/project
2020-06-16 10:17:50 +02:00
..
__pycache__ init commit 2019-10-24 14:01:43 +02:00
generated_music Add default folder and add history storing feature 2020-06-16 10:17:50 +02:00
midi_packs Add default folder and add history storing feature 2020-06-16 10:17:50 +02:00
models Add default folder and add history storing feature 2020-06-16 10:17:50 +02:00
training_sets Add default folder and add history storing feature 2020-06-16 10:17:50 +02:00
extract.py made it simplier to use 2019-10-30 16:21:36 +01:00
generate.py made it simplier to use 2019-10-30 16:21:36 +01:00
midi_processing.py made it simplier to use 2019-10-30 16:21:36 +01:00
model.py made it simplier to use 2019-10-30 16:21:36 +01:00
readme.md init commit 2019-10-24 14:01:43 +02:00
train.py Add default folder and add history storing feature 2020-06-16 10:17:50 +02:00

MUSIC GENERATION USING DEEP LEARNING

AUTHOR: CEZARY PUKOWNIK

How to use:

  1. In folder ./midi_packs make folder with midi files you want train on
  2. Use extract.py to export data from midis

./extract.py [str: midi_pack_name] [str: name_of_session] --b [int: seq_len] -a [analize data first]

  1. Use train.py to train model

./train.py [str: name_of_session] --b [int: batch_size] --l [int: latent_space] --e [int: epochs] --i [str: instrument] -r [reset]

  1. Use generate.py to generate music from models

./generate.py [str: name_of_session] --n [number of generations] --m [mode {'from_seq','from_state'}]