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.i18n import I18nAuto from infer.modules.vc.modules import VC 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) i18n = I18nAuto() i18n.print() load_dotenv() config = Config() vc = VC(config) weight_root = os.getenv("weight_root") weight_uvr5_root = os.getenv("weight_uvr5_root") index_root = "logs" 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()