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import os
import argparse
from tqdm import tqdm
from random import shuffle
import json
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/48k", help="path to source dir")
args = parser.parse_args()
previous_config = json.load(open("configs/config.json", "rb"))
train = []
val = []
test = []
idx = 0
spk_dict = previous_config["spk"]
spk_id = max([i for i in spk_dict.values()]) + 1
for speaker in tqdm(os.listdir(args.source_dir)):
if speaker not in spk_dict.keys():
spk_dict[speaker] = spk_id
spk_id += 1
wavs = [os.path.join(args.source_dir, speaker, i)for i in os.listdir(os.path.join(args.source_dir, speaker))]
wavs = [i for i in wavs if i.endswith("wav")]
shuffle(wavs)
train += wavs[2:-10]
val += wavs[:2]
test += wavs[-10:]
assert previous_config["model"]["n_speakers"] > len(spk_dict.keys())
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")
previous_config["spk"] = spk_dict
print("Writing configs/config.json")
with open("configs/config.json", "w") as f:
json.dump(previous_config, f, indent=2)
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