Neri_sovits4.0 / preprocess_flist_config.py
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import os
import argparse
import re
from tqdm import tqdm
from random import shuffle
import json
config_template = json.load(open("configs/config.json"))
pattern = re.compile(r'^[\.a-zA-Z0-9_\/]+$')
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("--train_list", type=str, default="./filelists/train.txt", help="path to train list")
parser.add_argument("--val_list", type=str, default="./filelists/val.txt", help="path to val list")
parser.add_argument("--test_list", type=str, default="./filelists/test.txt", help="path to test list")
parser.add_argument("--source_dir", type=str, default="./dataset/44k", help="path to source dir")
args = parser.parse_args()
train = []
val = []
test = []
idx = 0
spk_dict = {}
spk_id = 0
for speaker in tqdm(os.listdir(args.source_dir)):
spk_dict[speaker] = spk_id
spk_id += 1
wavs = ["/".join([args.source_dir, speaker, i]) for i in os.listdir(os.path.join(args.source_dir, speaker))]
for wavpath in wavs:
if not pattern.match(wavpath):
print(f"warning:文件名{wavpath}中包含非字母数字下划线,可能会导致错误。(也可能不会)")
if len(wavs) < 10:
print(f"warning:{speaker}数据集数量小于10条,请补充数据")
wavs = [i for i in wavs if i.endswith("wav")]
shuffle(wavs)
train += wavs[2:-2]
val += wavs[:2]
test += wavs[-2:]
shuffle(train)
shuffle(val)
shuffle(test)
print("Writing", args.train_list)
with open(args.train_list, "w") as f:
for fname in tqdm(train):
wavpath = fname
f.write(wavpath + "\n")
print("Writing", args.val_list)
with open(args.val_list, "w") as f:
for fname in tqdm(val):
wavpath = fname
f.write(wavpath + "\n")
print("Writing", args.test_list)
with open(args.test_list, "w") as f:
for fname in tqdm(test):
wavpath = fname
f.write(wavpath + "\n")
config_template["spk"] = spk_dict
print("Writing configs/config.json")
with open("configs/config.json", "w") as f:
json.dump(config_template, f, indent=2)