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import platform,os,traceback
import ffmpeg
import numpy as np
import gradio as gr
from tools.i18n.i18n import I18nAuto
import pandas as pd
i18n = I18nAuto(language=os.environ.get('language','Auto'))
def load_audio(file, sr):
try:
# https://github.com/openai/whisper/blob/main/whisper/audio.py#L26
# This launches a subprocess to decode audio while down-mixing and resampling as necessary.
# Requires the ffmpeg CLI and `ffmpeg-python` package to be installed.
file = clean_path(file) # 防止小白拷路径头尾带了空格和"和回车
if os.path.exists(file) == False:
raise RuntimeError(
"You input a wrong audio path that does not exists, please fix it!"
)
out, _ = (
ffmpeg.input(file, threads=0)
.output("-", format="f32le", acodec="pcm_f32le", ac=1, ar=sr)
.run(cmd=["ffmpeg", "-nostdin"], capture_stdout=True, capture_stderr=True)
)
except Exception as e:
traceback.print_exc()
raise RuntimeError(i18n("音频加载失败"))
return np.frombuffer(out, np.float32).flatten()
def clean_path(path_str:str):
if path_str.endswith(('\\','/')):
return clean_path(path_str[0:-1])
path_str = path_str.replace('/', os.sep).replace('\\', os.sep)
return path_str.strip(" ").strip('\'').strip("\n").strip('"').strip(" ").strip("\u202a")
def check_for_existance(file_list:list=None,is_train=False,is_dataset_processing=False):
files_status=[]
if is_train == True and file_list:
file_list.append(os.path.join(file_list[0],'2-name2text.txt'))
file_list.append(os.path.join(file_list[0],'3-bert'))
file_list.append(os.path.join(file_list[0],'4-cnhubert'))
file_list.append(os.path.join(file_list[0],'5-wav32k'))
file_list.append(os.path.join(file_list[0],'6-name2semantic.tsv'))
for file in file_list:
if os.path.exists(file):files_status.append(True)
else:files_status.append(False)
if sum(files_status)!=len(files_status):
if is_train:
for file,status in zip(file_list,files_status):
if status:pass
else:gr.Warning(file)
gr.Warning(i18n('以下文件或文件夹不存在'))
return False
elif is_dataset_processing:
if files_status[0]:
return True
elif not files_status[0]:
gr.Warning(file_list[0])
elif not files_status[1] and file_list[1]:
gr.Warning(file_list[1])
gr.Warning(i18n('以下文件或文件夹不存在'))
return False
else:
if file_list[0]:
gr.Warning(file_list[0])
gr.Warning(i18n('以下文件或文件夹不存在'))
else:
gr.Warning(i18n('路径不能为空'))
return False
return True
def check_details(path_list=None,is_train=False,is_dataset_processing=False):
if is_dataset_processing:
list_path, audio_path = path_list
if (not list_path.endswith('.list')):
gr.Warning(i18n('请填入正确的List路径'))
return
if audio_path:
if not os.path.isdir(audio_path):
gr.Warning(i18n('请填入正确的音频文件夹路径'))
return
with open(list_path,"r",encoding="utf8")as f:
line=f.readline().strip("\n").split("\n")
wav_name, _, __, ___ = line[0].split("|")
wav_name=clean_path(wav_name)
if (audio_path != "" and audio_path != None):
wav_name = os.path.basename(wav_name)
wav_path = "%s/%s"%(audio_path, wav_name)
else:
wav_path=wav_name
if os.path.exists(wav_path):
...
else:
gr.Warning(i18n('路径错误'))
return
if is_train:
path_list.append(os.path.join(path_list[0],'2-name2text.txt'))
path_list.append(os.path.join(path_list[0],'4-cnhubert'))
path_list.append(os.path.join(path_list[0],'5-wav32k'))
path_list.append(os.path.join(path_list[0],'6-name2semantic.tsv'))
phone_path, hubert_path, wav_path, semantic_path = path_list[1:]
with open(phone_path,'r',encoding='utf-8') as f:
if f.read(1):...
else:gr.Warning(i18n('缺少音素数据集'))
if os.listdir(hubert_path):...
else:gr.Warning(i18n('缺少Hubert数据集'))
if os.listdir(wav_path):...
else:gr.Warning(i18n('缺少音频数据集'))
df = pd.read_csv(
semantic_path, delimiter="\t", encoding="utf-8"
)
if len(df) >= 1:...
else:gr.Warning(i18n('缺少语义数据集'))
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