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"""preprocess_mir_st500.py"""
import os
import json
from typing import Dict
import numpy as np
from utils.audio import get_audio_file_info, load_audio_file
from utils.midi import midi2note, note_event2midi
from utils.note2event import note2note_event, sort_notes, validate_notes, trim_overlapping_notes
from utils.event2note import event2note_event
from utils.note_event_dataclasses import Note, NoteEvent
from utils.utils import note_event2token2note_event_sanity_check
SINGING_WITH_UNANNOTATED_PROGRAM = [100, 129] # 100 for singing voice, 129 for unannotated
SINGING_ONLY_PROGRAM = [100]
def check_file_existence(file: str) -> bool:
"""Checks if file exists."""
res = True
if not os.path.exists(file):
res = False
elif get_audio_file_info(file)[1] < 10 * 16000:
print(f'File {file} is too short.')
res = False
return res
def create_spleeter_audio_stem(vocal_audio_file, accomp_audio_file, mir_st500_id) -> Dict:
program = SINGING_WITH_UNANNOTATED_PROGRAM
is_drum = [0, 0]
audio_tracks = [] # multi-channel audio array (C, T)
vocal_audio = load_audio_file(vocal_audio_file, dtype=np.int16) / 2**15 # returns bytes
audio_tracks.append(vocal_audio.astype(np.float16))
accomp_audio = load_audio_file(accomp_audio_file, dtype=np.int16) / 2**15 # returns bytes
audio_tracks.append(accomp_audio.astype(np.float16))
max_length = max(len(vocal_audio), len(accomp_audio))
# collate all the audio tracks into a single array
n_tracks = 2
audio_array = np.zeros((n_tracks, max_length), dtype=np.float16)
for j, audio in enumerate(audio_tracks):
audio_array[j, :len(audio)] = audio
stem_content = {
'mir_st500_id': mir_st500_id,
'program': np.array(program, dtype=np.int64),
'is_drum': np.array(is_drum, dtype=np.int64),
'n_frames': max_length, # int
'audio_array': audio_array # (n_tracks, n_frames)
}
return stem_content
def create_note_note_event_midi_from_mir_st500_annotation(ann, midi_file, mir_st500_id):
"""
Args:
ann: List[List[float, float, float]] # [onset, offset, pitch]
mir_st500_id: str
Returns:
notes: List[Note]
note_events: List[NoteEvent]
midi: List[List[int]]
"""
notes = []
for onset, offset, pitch in ann:
notes.append(
Note(
is_drum=False,
program=100,
onset=float(onset),
offset=float(offset),
pitch=int(pitch),
velocity=1))
notes = sort_notes(notes)
notes = validate_notes(notes)
notes = trim_overlapping_notes(notes)
note_events = note2note_event(notes)
# Write midi file
note_event2midi(note_events, midi_file)
print(f"Created {midi_file}")
return { # notes
'mir_st500_id': mir_st500_id,
'program': SINGING_ONLY_PROGRAM,
'is_drum': [0, 0],
'duration_sec': note_events[-1].time,
'notes': notes,
}, { # note_events
'mir_st500_id': mir_st500_id,
'program': SINGING_ONLY_PROGRAM,
'is_drum': [0, 0],
'duration_sec': note_events[-1].time,
'note_events': note_events,
}
def correct_ann(ann_all: Dict, fix_offset: bool = False, max_dur: float = 0.5):
""" correct too short notes that are actully sung in legato """
for i in range(1, 101):
for j, v in enumerate(ann_all[str(i)]):
dur = v[1] - v[0]
if dur < 0.01:
next_onset = ann_all[str(i)][j + 1][0]
dist_to_next_onset = next_onset - v[1]
if fix_offset is True:
if dist_to_next_onset < max_dur:
# correct the offset
ann_all[str(i)][j][1] = next_onset
print(f'Corrected track {i}: {v} to {ann_all[str(i)][j]}')
else:
print(v, ann_all[str(i)][j + 1], f'dist_to_next_onset: {dist_to_next_onset}')
def preprocess_mir_st500_16k(data_home=os.PathLike,
dataset_name='mir_st500',
apply_correction=False,
sanity_check=False) -> None:
"""
Splits:
'train',
'train_vocal',
'train_stem',
'test',
'test_vocal',
'all',
'all_vocal',
'all_stem'
Writes:
- {dataset_name}_{split}_file_list.json: a dictionary with the following keys:
{
index:
{
'mir_st500_id': mir_st500_id,
'n_frames': (int),
'mix_audio_file': 'path/to/mix.wav',
'notes_file': 'path/to/notes.npy',
'note_events_file': 'path/to/note_events.npy',
'midi_file': 'path/to/midi.mid',
'program': List[int], 100 for singing voice, and 129 for unannotated
'is_drum': List[int], # [0] or [1]
}
}
"""
# Directory and file paths
base_dir = os.path.join(data_home, dataset_name + '_yourmt3_16k')
output_index_dir = os.path.join(data_home, 'yourmt3_indexes')
os.makedirs(output_index_dir, exist_ok=True)
# Load annotation json file as dictionary
ann_file = os.path.join(base_dir, 'MIR-ST500_20210206', 'MIR-ST500_corrected.json')
with open(ann_file, 'r') as f:
ann_all = json.load(f) # index "1" to "500"
# Correction for annotation
correct_ann(ann_all, fix_offset=apply_correction, max_dur=0.5)
# Check missing audio files and create a dictionary
audio_all = {} # except for missing files
audio_missing = {'train': [], 'test': []}
for i in range(1, 501):
split = 'train' if i < 401 else 'test'
audio_file = os.path.join(base_dir, f'{split}', f'{i}', 'converted_Mixture.wav')
audio_vocal_file = os.path.join(base_dir, f'{split}', f'{i}', 'vocals.wav')
audio_acc_file = os.path.join(base_dir, f'{split}', f'{i}', 'accompaniment.wav')
if check_file_existence(audio_file) and check_file_existence(
audio_vocal_file) and check_file_existence(audio_acc_file):
audio_all[str(i)] = audio_file
else:
audio_missing[split].append(i)
print(
f'Number of missing audio files: train = {len(audio_missing["train"])}, test = {len(audio_missing["test"])}'
)
assert len(audio_all.keys()) == 500
# Track ids
ids_all = audio_all.keys()
ids_train = []
ids_test = []
for i in ids_all:
if int(i) < 401:
ids_train.append(i)
else:
ids_test.append(i)
# assert len(ids_train) == 346 and len(ids_test) == 94
assert len(ids_train) == 400 and len(ids_test) == 100
# Create notes, note_events, and MIDI from annotation
for id in ids_all:
ann = ann_all[id]
split = 'train' if int(id) < 401 else 'test'
midi_file = os.path.join(base_dir, f'{split}', id, 'singing.mid')
notes, note_events = create_note_note_event_midi_from_mir_st500_annotation(
ann, midi_file, id)
notes_file = midi_file.replace('.mid', '_notes.npy')
note_events_file = midi_file.replace('.mid', '_note_events.npy')
np.save(notes_file, notes, allow_pickle=True, fix_imports=False)
print(f"Created {notes_file}")
np.save(note_events_file, note_events, allow_pickle=True, fix_imports=False)
print(f"Created {note_events_file}")
if sanity_check:
# sanity check
print(f'Sanity check for {id}...')
note_event2token2note_event_sanity_check(note_events['note_events'], notes['notes'])
# Process audio files
for id in ids_all:
split = 'train' if int(id) < 401 else 'test'
audio_vocal_file = os.path.join(base_dir, f'{split}', id, 'vocals.wav')
audio_acc_file = os.path.join(base_dir, f'{split}', id, 'accompaniment.wav')
stem_file = os.path.join(base_dir, f'{split}', id, 'stem.npy')
stem_content = create_spleeter_audio_stem(audio_vocal_file, audio_acc_file, id)
# write audio stem
np.save(stem_file, stem_content, allow_pickle=True, fix_imports=False)
print(f"Created {stem_file}")
# Create file_list.json
ids_by_split = {
'train': ids_train,
'train_vocal': ids_train,
'train_stem': ids_train,
'test': ids_test,
'test_vocal': ids_test,
'all': ids_all,
'all_vocal': ids_all,
'all_stem': ids_all
}
for split in [
'train', 'train_vocal', 'train_stem', 'test', 'test_vocal', 'all', 'all_vocal',
'all_stem'
]:
file_list = {}
for i, id in enumerate(ids_by_split[split]):
wav_file = audio_all[id]
n_frames = get_audio_file_info(wav_file)[1]
if 'vocal' in split:
stem_file = None
wav_file = wav_file.replace('converted_Mixture.wav', 'vocals.wav')
program = SINGING_ONLY_PROGRAM
is_drum = [0]
elif 'stem' in split:
stem_file = wav_file.replace('converted_Mixture.wav', 'stem.npy')
program = SINGING_WITH_UNANNOTATED_PROGRAM
is_drum = [0, 0]
else:
stem_file = None
program = SINGING_WITH_UNANNOTATED_PROGRAM
is_drum = [0, 0]
mid_file = os.path.join(os.path.dirname(wav_file), 'singing.mid')
file_list[i] = {
'mir_st500_id': id,
'n_frames': n_frames,
'stem_file': stem_file,
'mix_audio_file': wav_file,
'notes_file': mid_file.replace('.mid', '_notes.npy'),
'note_events_file': mid_file.replace('.mid', '_note_events.npy'),
'midi_file': mid_file,
'program': program,
'is_drum': is_drum,
}
if stem_file is None:
del file_list[i]['stem_file']
output_file = os.path.join(output_index_dir, f'{dataset_name}_{split}_file_list.json')
with open(output_file, 'w') as f:
json.dump(file_list, f, indent=4)
print(f'Created {output_file}') |