Upload rebuild.py

rebuild.py

@@ -0,0 +1,161 @@
+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)
+logger = logging.getLogger(__name__)
+
+i18n = I18nAuto()
+logger.info(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()