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import argparse
import json
import os
import re
import wave
from random import shuffle
from loguru import logger
from tqdm import tqdm
import diffusion.logger.utils as du
pattern = re.compile(r'^[\.a-zA-Z0-9_\/]+$')
def get_wav_duration(file_path):
try:
with wave.open(file_path, 'rb') as wav_file:
# 获取音频帧数
n_frames = wav_file.getnframes()
# 获取采样率
framerate = wav_file.getframerate()
# 计算时长（秒）
return n_frames / float(framerate)
except Exception as e:
logger.error(f"Reading {file_path}")
raise e
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("--source_dir", type=str, default="./dataset/44k", help="path to source dir")
parser.add_argument("--speech_encoder", type=str, default="vec768l12", help="choice a speech encoder|'vec768l12','vec256l9','hubertsoft','whisper-ppg','cnhubertlarge','dphubert','whisper-ppg-large','wavlmbase+'")
parser.add_argument("--vol_aug", action="store_true", help="Whether to use volume embedding and volume augmentation")
parser.add_argument("--tiny", action="store_true", help="Whether to train sovits tiny")
args = parser.parse_args()
config_template = json.load(open("configs_template/config_tiny_template.json")) if args.tiny else json.load(open("configs_template/config_template.json"))
train = []
val = []
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 = []
for file_name in os.listdir(os.path.join(args.source_dir, speaker)):
if not file_name.endswith("wav"):
continue
if file_name.startswith("."):
continue
file_path = "/".join([args.source_dir, speaker, file_name])
if not pattern.match(file_name):
logger.warning("Detected non-ASCII file name: " + file_path)
if get_wav_duration(file_path) < 0.3:
logger.info("Skip too short audio: " + file_path)
continue
wavs.append(file_path)
shuffle(wavs)
train += wavs[2:]
val += wavs[:2]
shuffle(train)
shuffle(val)
logger.info("Writing " + args.train_list)
with open(args.train_list, "w") as f:
for fname in tqdm(train):
wavpath = fname
f.write(wavpath + "\n")
logger.info("Writing " + args.val_list)
with open(args.val_list, "w") as f:
for fname in tqdm(val):
wavpath = fname
f.write(wavpath + "\n")
d_config_template = du.load_config("configs_template/diffusion_template.yaml")
d_config_template["model"]["n_spk"] = spk_id
d_config_template["data"]["encoder"] = args.speech_encoder
d_config_template["spk"] = spk_dict
config_template["spk"] = spk_dict
config_template["model"]["n_speakers"] = spk_id
config_template["model"]["speech_encoder"] = args.speech_encoder
if args.speech_encoder == "vec768l12" or args.speech_encoder == "dphubert" or args.speech_encoder == "wavlmbase+":
config_template["model"]["ssl_dim"] = config_template["model"]["filter_channels"] = config_template["model"]["gin_channels"] = 768
d_config_template["data"]["encoder_out_channels"] = 768
elif args.speech_encoder == "vec256l9" or args.speech_encoder == 'hubertsoft':
config_template["model"]["ssl_dim"] = config_template["model"]["gin_channels"] = 256
d_config_template["data"]["encoder_out_channels"] = 256
elif args.speech_encoder == "whisper-ppg" or args.speech_encoder == 'cnhubertlarge':
config_template["model"]["ssl_dim"] = config_template["model"]["filter_channels"] = config_template["model"]["gin_channels"] = 1024
d_config_template["data"]["encoder_out_channels"] = 1024
elif args.speech_encoder == "whisper-ppg-large":
config_template["model"]["ssl_dim"] = config_template["model"]["filter_channels"] = config_template["model"]["gin_channels"] = 1280
d_config_template["data"]["encoder_out_channels"] = 1280
if args.vol_aug:
config_template["train"]["vol_aug"] = config_template["model"]["vol_embedding"] = True
if args.tiny:
config_template["model"]["filter_channels"] = 512
logger.info("Writing to configs/config.json")
with open("configs/config.json", "w") as f:
json.dump(config_template, f, indent=2)
logger.info("Writing to configs/diffusion.yaml")
du.save_config("configs/diffusion.yaml",d_config_template)
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