praca-magisterska/midi_to_samples.py
2019-05-08 08:03:52 +02:00

77 lines
2.7 KiB
Python

import settings
import pypianoroll as roll
import matplotlib.pyplot as plt
import numpy as np
import os
from math import floor
MIDI_DIRECTORY = settings.midi_path
SAMPLES_DIRECTORY = settings.samples_path
MIDI_RESOLUTION = settings.midi_resolution
BEAT_PER_BATCH = settings.beats_per_sample
samples = np.empty((0,BEAT_PER_BATCH,96,128))
def erase_note_lenth(pianoroll):
if pianoroll.ndim != 2:
raise ValueError('pianoroll should be two dimentional')
now_block = []
for x in pianoroll:
this = None
prev = None
new_line =[]
for y in x:
this = y
if prev != None:
if this > 0 and prev > 0:
new_line.append(0)
else:
new_line.append(y)
else:
new_line.append(y)
prev = this
now_block.append(new_line)
return np.array(now_block)
print('Start convertion')
for midi_file in os.listdir(MIDI_DIRECTORY):
try:
print('Reading file: {}'.format(midi_file))
song = roll.Multitrack('{}/{}'.format(MIDI_DIRECTORY, midi_file))
# no_drums_mt = roll.Multitrack(tempo=120.0, downbeat=[0, 96, 192, 288], beat_resolution=24)
intruments_only = roll.Multitrack(tempo=120.0, beat_resolution=24)
for track in song.tracks:
if track.is_drum == False:
print(track.name, track.program)
intruments_only.append_track(track=track, pianoroll=track.pianoroll)
instrument_track = track.pianoroll
# plt.imshow(instrument_track[24*8:24*24].T)
# plt.savefig('data/0_{}.png'.format(midi_file))
instrument_track = erase_note_lenth(instrument_track.T).T
# plt.imshow(instrument_track[24*8:24*24].T)
# plt.savefig('data/1_{}.png'.format(midi_file))
# instruments = no_drums_mt.get_merged_pianoroll(mode='sum')
beats = floor( (instrument_track.shape[0] / MIDI_RESOLUTION) / BEAT_PER_BATCH) * BEAT_PER_BATCH
notes_for_beats = beats * MIDI_RESOLUTION
print('beats: ', beats)
samples_of_song = np.asarray(np.split(instrument_track[:notes_for_beats], beats))
samples_of_song = samples_of_song.reshape(int(beats/BEAT_PER_BATCH),BEAT_PER_BATCH,96,128)
print('Converted samples: {}'.format(samples_of_song.shape))
samples = np.concatenate([samples_of_song,samples], axis=0)
np.savez_compressed(SAMPLES_DIRECTORY,samples)
except Exception as error:
print('Convertion faild: {}'.format(error))
pass
finally:
print('Done!')