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import logging |
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import os |
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import gradio as gr |
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from dotenv import load_dotenv |
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from assets.configs.config import Config |
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from assets.i18n.i18n import I18nAuto |
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from lib.infer.modules.vc.pipeline import Pipeline |
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VC = Pipeline |
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logging.getLogger("numba").setLevel(logging.WARNING) |
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logging.getLogger("markdown_it").setLevel(logging.WARNING) |
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logging.getLogger("urllib3").setLevel(logging.WARNING) |
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logging.getLogger("matplotlib").setLevel(logging.WARNING) |
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logger = logging.getLogger(__name__) |
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i18n = I18nAuto() |
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load_dotenv() |
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config = Config() |
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vc = VC(config) |
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weight_root = os.getenv("weight_root") |
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weight_uvr5_root = os.getenv("weight_uvr5_root") |
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index_root = os.getenv("index_root") |
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names = [] |
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hubert_model = None |
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for name in os.listdir(weight_root): |
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if name.endswith(".pth"): |
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names.append(name) |
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index_paths = [] |
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for root, dirs, files in os.walk(index_root, topdown=False): |
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for name in files: |
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if name.endswith(".index") and "trained" not in name: |
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index_paths.append("%s/%s" % (root, name)) |
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app = gr.Blocks() |
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with app: |
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with gr.Tabs(): |
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with gr.TabItem("在线demo"): |
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gr.Markdown( |
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value=""" |
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RVC 在线demo |
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""" |
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) |
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sid = gr.Dropdown(label=i18n("推理音色"), choices=sorted(names)) |
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with gr.Column(): |
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spk_item = gr.Slider( |
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minimum=0, |
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maximum=2333, |
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step=1, |
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label=i18n("请选择说话人id"), |
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value=0, |
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visible=False, |
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interactive=True, |
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) |
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sid.change(fn=vc.get_vc, inputs=[sid], outputs=[spk_item]) |
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gr.Markdown( |
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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. ") |
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) |
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vc_input3 = gr.Audio(label="上传音频（长度小于90秒）") |
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vc_transform0 = gr.Number(label=i18n("变调(整数, 半音数量, 升八度12降八度-12)"), value=0) |
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f0method0 = gr.Radio( |
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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"), |
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choices=["pm", "harvest", "crepe", "rmvpe"], |
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value="pm", |
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interactive=True, |
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) |
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filter_radius0 = gr.Slider( |
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minimum=0, |
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maximum=7, |
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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"), |
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value=3, |
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step=1, |
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interactive=True, |
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) |
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with gr.Column(): |
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file_index1 = gr.Textbox( |
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label=i18n("特征检索库文件路径,为空则使用下拉的选择结果"), |
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value="", |
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interactive=False, |
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visible=False, |
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) |
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file_index2 = gr.Dropdown( |
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label=i18n("自动检测index路径,下拉式选择(dropdown)"), |
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choices=sorted(index_paths), |
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interactive=True, |
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) |
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index_rate1 = gr.Slider( |
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minimum=0, |
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maximum=1, |
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label=i18n("检索特征占比"), |
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value=0.88, |
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interactive=True, |
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) |
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resample_sr0 = gr.Slider( |
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minimum=0, |
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maximum=48000, |
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label=i18n("后处理重采样至最终采样率，0为不进行重采样"), |
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value=0, |
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step=1, |
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interactive=True, |
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) |
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rms_mix_rate0 = gr.Slider( |
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minimum=0, |
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maximum=1, |
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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"), |
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value=1, |
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interactive=True, |
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) |
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protect0 = gr.Slider( |
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minimum=0, |
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maximum=0.5, |
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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"), |
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value=0.33, |
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step=0.01, |
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interactive=True, |
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) |
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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")) |
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but0 = gr.Button(i18n("转换"), variant="primary") |
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vc_output1 = gr.Textbox(label=i18n("输出信息")) |
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vc_output2 = gr.Audio(label=i18n("输出音频(右下角三个点,点了可以下载)")) |
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but0.click( |
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vc.vc_single, |
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[ |
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spk_item, |
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vc_input3, |
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vc_transform0, |
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f0_file, |
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f0method0, |
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file_index1, |
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file_index2, |
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index_rate1, |
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filter_radius0, |
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resample_sr0, |
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rms_mix_rate0, |
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protect0, |
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], |
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[vc_output1, vc_output2], |
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) |
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app.launch() |
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