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# Copyright (c) 2023 Amphion.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import os
import json
import torchaudio
import librosa
from tqdm import tqdm
from glob import glob
from collections import defaultdict
from utils.util import has_existed
from preprocessors import GOLDEN_TEST_SAMPLES
def get_test_songs():
golden_samples = GOLDEN_TEST_SAMPLES["popbutfy"]
# every item is a tuple (singer, song)
golden_songs = [s.split("#")[:2] for s in golden_samples]
# singer#song, eg: Female1#Almost_lover_Amateur
return golden_songs
def popbutfy_statistics(data_dir):
singers = []
songs = []
singer2songs = defaultdict(lambda: defaultdict(list))
data_infos = glob(data_dir + "/*")
for data_info in data_infos:
data_info_split = data_info.split("/")[-1].split("#")
singer, song = data_info_split[0], data_info_split[-1]
singers.append(singer)
songs.append(song)
utts = glob(data_info + "/*")
for utt in utts:
uid = utt.split("/")[-1].split("_")[-1].split(".")[0]
singer2songs[singer][song].append(uid)
unique_singers = list(set(singers))
unique_songs = list(set(songs))
unique_singers.sort()
unique_songs.sort()
print(
"PopBuTFy: {} singers, {} utterances ({} unique songs)".format(
len(unique_singers), len(songs), len(unique_songs)
)
)
print("Singers: \n{}".format("\t".join(unique_singers)))
return singer2songs, unique_singers
def main(output_path, dataset_path):
print("-" * 10)
print("Preparing test samples for popbutfy...\n")
save_dir = os.path.join(output_path, "popbutfy")
os.makedirs(save_dir, exist_ok=True)
train_output_file = os.path.join(save_dir, "train.json")
test_output_file = os.path.join(save_dir, "test.json")
singer_dict_file = os.path.join(save_dir, "singers.json")
utt2singer_file = os.path.join(save_dir, "utt2singer")
if (
has_existed(train_output_file)
and has_existed(test_output_file)
and has_existed(singer_dict_file)
and has_existed(utt2singer_file)
):
return
utt2singer = open(utt2singer_file, "w")
# Load
popbutfy_dir = dataset_path
singer2songs, unique_singers = popbutfy_statistics(popbutfy_dir)
test_songs = get_test_songs()
# We select songs of standard samples as test songs
train = []
test = []
train_index_count = 0
test_index_count = 0
train_total_duration = 0
test_total_duration = 0
for singer, songs in tqdm(singer2songs.items()):
song_names = list(songs.keys())
for chosen_song in song_names:
for chosen_uid in songs[chosen_song]:
res = {
"Dataset": "popbutfy",
"Singer": singer,
"Song": chosen_song,
"Uid": "{}#{}#".format(singer, chosen_song, chosen_uid),
}
res["Path"] = "{}#singing#{}/{}#singing#{}_{}.mp3".format(
singer, chosen_song, singer, chosen_song, chosen_uid
)
if not os.path.exists(os.path.join(popbutfy_dir, res["Path"])):
res["Path"] = "{}#singing#{}/{}#singing#{}_{}.wav".format(
singer, chosen_song, singer, chosen_song, chosen_uid
)
res["Path"] = os.path.join(popbutfy_dir, res["Path"])
assert os.path.exists(res["Path"])
if res["Path"].split("/")[-1].split(".")[-1] == "wav":
waveform, sample_rate = torchaudio.load(res["Path"])
duration = waveform.size(-1) / sample_rate
else:
waveform, sample_rate = librosa.load(res["Path"])
duration = waveform.shape[-1] / sample_rate
res["Duration"] = duration
if ([singer, chosen_song]) in test_songs:
res["index"] = test_index_count
test_total_duration += duration
test.append(res)
test_index_count += 1
else:
res["index"] = train_index_count
train_total_duration += duration
train.append(res)
train_index_count += 1
utt2singer.write("{}\t{}\n".format(res["Uid"], res["Singer"]))
print("#Train = {}, #Test = {}".format(len(train), len(test)))
print(
"#Train hours= {}, #Test hours= {}".format(
train_total_duration / 3600, test_total_duration / 3600
)
)
# Save train.json and test.json
with open(train_output_file, "w") as f:
json.dump(train, f, indent=4, ensure_ascii=False)
with open(test_output_file, "w") as f:
json.dump(test, f, indent=4, ensure_ascii=False)
# Save singers.json
singer_lut = {name: i for i, name in enumerate(unique_singers)}
with open(singer_dict_file, "w") as f:
json.dump(singer_lut, f, indent=4, ensure_ascii=False)
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