def event_indeces_to_midi_file(event_indeces, midi_file_name, velocity_scale=0.8):
event_seq = EventSeq.from_array(event_indeces)
note_seq = event_seq.to_note_seq()
for note in note_seq.notes:
note.velocity = int((note.velocity - 64) * velocity_scale + 64)
note_seq.to_midi_file(midi_file_name)
return len(note_seq.notes)
return
except:
print(' Error')
continue
for path, future in Bar('Processing').iter(results):
print(' ', end='[{}]'.format(path), flush=True)
name = os.path.basename(path)
code = hashlib.md5(path.encode()).hexdigest()
save_path = os.path.join(save_dir, out_fmt.format(name, code))
torch.save(future.result(), save_path)
print('Done')
"""
if __name__ == '__main__':
"""
preprocess_midi_files_under(
midi_root=sys.argv[1],
save_dir=sys.argv[2],
num_workers=int(sys.argv[3],
type='event'))
"""
path = "../../../egs/dataset/tmp_res/test_seq_bef.midi"
save_path = "../../../egs/dataset/tmp_res/test_seq_aft.midi"
event_seq_array = preprocess_midi_event(path)
event_seq = EventSeq.from_array(event_seq_array)
note_seq = event_seq.to_note_seq()
note_seq.to_midi_file(save_path)