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import logging | |
import os | |
# os.system("wget -P cvec/ https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/hubert_base.pt") | |
import gradio as gr | |
from dotenv import load_dotenv | |
from configs.config import Config | |
from i18n import I18nAuto | |
from infer.modules.vc.pipeline import Pipeline | |
VC = Pipeline | |
logging.getLogger("numba").setLevel(logging.WARNING) | |
logging.getLogger("markdown_it").setLevel(logging.WARNING) | |
logging.getLogger("urllib3").setLevel(logging.WARNING) | |
logging.getLogger("matplotlib").setLevel(logging.WARNING) | |
logger = logging.getLogger(__name__) | |
i18n = I18nAuto() | |
#(i18n) | |
load_dotenv() | |
config = Config() | |
vc = VC(config) | |
weight_root = os.getenv("weight_root") | |
weight_uvr5_root = os.getenv("weight_uvr5_root") | |
index_root = os.getenv("index_root") | |
names = [] | |
hubert_model = None | |
for name in os.listdir(weight_root): | |
if name.endswith(".pth"): | |
names.append(name) | |
index_paths = [] | |
for root, dirs, files in os.walk(index_root, topdown=False): | |
for name in files: | |
if name.endswith(".index") and "trained" not in name: | |
index_paths.append("%s/%s" % (root, name)) | |
app = gr.Blocks() | |
with app: | |
with gr.Tabs(): | |
with gr.TabItem("在线demo"): | |
gr.Markdown( | |
value=""" | |
RVC 在线demo | |
""" | |
) | |
sid = gr.Dropdown(label=i18n("推理音色"), choices=sorted(names)) | |
with gr.Column(): | |
spk_item = gr.Slider( | |
minimum=0, | |
maximum=2333, | |
step=1, | |
label=i18n("请选择说话人id"), | |
value=0, | |
visible=False, | |
interactive=True, | |
) | |
sid.change(fn=vc.get_vc, inputs=[sid], outputs=[spk_item]) | |
gr.Markdown( | |
value=i18n("男转女推荐+12key, 女转男推荐-12key, 如果音域爆炸导致音色失真也可以自己调整到合适音域. ") | |
) | |
vc_input3 = gr.Audio(label="上传音频(长度小于90秒)") | |
vc_transform0 = gr.Number(label=i18n("变调(整数, 半音数量, 升八度12降八度-12)"), value=0) | |
f0method0 = gr.Radio( | |
label=i18n("选择音高提取算法,输入歌声可用pm提速,harvest低音好但巨慢无比,crepe效果好但吃GPU"), | |
choices=["pm", "harvest", "crepe", "rmvpe"], | |
value="pm", | |
interactive=True, | |
) | |
filter_radius0 = gr.Slider( | |
minimum=0, | |
maximum=7, | |
label=i18n(">=3则使用对harvest音高识别的结果使用中值滤波,数值为滤波半径,使用可以削弱哑音"), | |
value=3, | |
step=1, | |
interactive=True, | |
) | |
with gr.Column(): | |
file_index1 = gr.Textbox( | |
label=i18n("特征检索库文件路径,为空则使用下拉的选择结果"), | |
value="", | |
interactive=False, | |
visible=False, | |
) | |
file_index2 = gr.Dropdown( | |
label=i18n("自动检测index路径,下拉式选择(dropdown)"), | |
choices=sorted(index_paths), | |
interactive=True, | |
) | |
index_rate1 = gr.Slider( | |
minimum=0, | |
maximum=1, | |
label=i18n("检索特征占比"), | |
value=0.88, | |
interactive=True, | |
) | |
resample_sr0 = gr.Slider( | |
minimum=0, | |
maximum=48000, | |
label=i18n("后处理重采样至最终采样率,0为不进行重采样"), | |
value=0, | |
step=1, | |
interactive=True, | |
) | |
rms_mix_rate0 = gr.Slider( | |
minimum=0, | |
maximum=1, | |
label=i18n("输入源音量包络替换输出音量包络融合比例,越靠近1越使用输出包络"), | |
value=1, | |
interactive=True, | |
) | |
protect0 = gr.Slider( | |
minimum=0, | |
maximum=0.5, | |
label=i18n("保护清辅音和呼吸声,防止电音撕裂等artifact,拉满0.5不开启,调低加大保护力度但可能降低索引效果"), | |
value=0.33, | |
step=0.01, | |
interactive=True, | |
) | |
f0_file = gr.File(label=i18n("F0曲线文件, 可选, 一行一个音高, 代替默认F0及升降调")) | |
but0 = gr.Button(i18n("转换"), variant="primary") | |
vc_output1 = gr.Textbox(label=i18n("输出信息")) | |
vc_output2 = gr.Audio(label=i18n("输出音频(右下角三个点,点了可以下载)")) | |
but0.click( | |
vc.vc_single, | |
[ | |
spk_item, | |
vc_input3, | |
vc_transform0, | |
f0_file, | |
f0method0, | |
file_index1, | |
file_index2, | |
# file_big_npy1, | |
index_rate1, | |
filter_radius0, | |
resample_sr0, | |
rms_mix_rate0, | |
protect0, | |
], | |
[vc_output1, vc_output2], | |
) | |
app.launch() | |