def __getitem__(self, index):
full_filename = self.full_filenames[index]
multitrack = Multitrack(full_filename)
multitrack.clip(0, 1)
piano_roll = multitrack.tracks[0].pianoroll[::6, :]
return torch.FloatTensor(piano_roll.astype(float))
def converter(file):
phrase_size = BAR_SIZE * PHRASE_SIZE
try:
midi_md5 = os.path.splitext(
os.path.basename(os.path.join(MIDI_FILE_PATH, file)))[0]
multitrack = Multitrack(beat_resolution=BEAT_RESOLUTION, name=midi_md5)
pm = pretty_midi.PrettyMIDI(os.path.join(MIDI_FILE_PATH, file))
multitrack.parse_pretty_midi(pm)
midi_info = get_midi_info(pm)
length = multitrack.get_max_length()
padding_size = phrase_size - (
length % phrase_size) if length % phrase_size else 0
tmp = length // phrase_size + (1 if length % phrase_size else 0)
multitrack.clip(0, 127)
data = multitrack.get_merged_pianoroll(mode='max')
if padding_size:
data = np.concatenate((data,
np.array([[0 for _ in range(128)]
for _ in range(padding_size)])),
axis=0)
data.astype(np.float64)
data = data / 127.
data[data < 0.35] = 0.
data[data >= 0.35] = 1.
data_by_phrase = []
phrase_number = [330] + [i for i in range(tmp - 2, -1, -1)]
for i in range(0, len(data), phrase_size):
data_by_phrase.append(data[i:i + phrase_size])
with open(
os.path.join(NP_FILE_PATH, '{}_{}.pkl'.format(tmp, midi_md5)),
'wb') as fp:
pickle.dump([np.array(data_by_phrase), phrase_number], fp)
return (midi_md5, midi_info)
except Exception as e:
print(e)
return None
