Retrieval_based_Voice_Conversion_WebUI.ipynb · chawuNG/Retrieval-based-Voice-Conversion-WebUI

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文件

.github/workflows

TEMP

__pycache__

configs

docs

i18n

infer

infer_pack

logs

runtime

train

uvr5_pack

weights

.gitattributes

.gitignore

Changelog_CN.md

LICENSE

README.md

Retrieval_based_Voice_Conversion_WebUI.ipynb

config.py

easy-infer.py

envfilescheck.bat

export_onnx.py

export_onnx_old.py

extract_f0_print.py

extract_feature_print.py

extract_locale.py

go-realtime-gui.bat

go-web.bat

gui.py

hubert_base.pt

i18n.py

infer-web-multi.py

infer-web.py

infer_uvr5.py

my_utils.py

poetry.lock

pyproject.toml

requirements-win-for-realtime_vc_gui.txt

requirements.txt

slicer2.py

train_nsf_sim_cache_sid_load_pretrain.py

trainset_preprocess_pipeline_print.py

vc_infer_pipeline.py

使用需遵守的协议-LICENSE.txt

克隆/下载

Retrieval_based_Voice_Conversion_WebUI.ipynb 16.06 KB

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "private_outputs": true,
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU",
    "gpuClass": "standard"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/liujing04/Retrieval-based-Voice-Conversion-WebUI/blob/main/Retrieval_based_Voice_Conversion_WebUI.ipynb)"
      ],
      "metadata": {
        "id": "ZFFCx5J80SGa"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "GmFP6bN9dvOq"
      },
      "outputs": [],
      "source": [
        "#@title 查看显卡\n",
        "!nvidia-smi"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#@title 安装依赖\n",
        "!apt-get -y install build-essential python3-dev ffmpeg\n",
        "!pip3 install --upgrade setuptools wheel\n",
        "!pip3 install --upgrade pip\n",
        "!pip3 install faiss-gpu fairseq gradio ffmpeg ffmpeg-python praat-parselmouth pyworld numpy==1.23.5 numba==0.56.4 librosa==0.9.2"
      ],
      "metadata": {
        "id": "wjddIFr1oS3W"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@title 克隆仓库\n",
        "\n",
        "!git clone --depth=1 -b stable https://github.com/fumiama/Retrieval-based-Voice-Conversion-WebUI\n",
        "%cd /content/Retrieval-based-Voice-Conversion-WebUI\n",
        "!mkdir -p pretrained uvr5_weights"
      ],
      "metadata": {
        "id": "ge_97mfpgqTm"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@title 更新仓库（一般无需执行）\n",
        "!git pull"
      ],
      "metadata": {
        "id": "BLDEZADkvlw1"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@title 安装aria2\n",
        "!apt -y install -qq aria2"
      ],
      "metadata": {
        "id": "pqE0PrnuRqI2"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@title 下载底模\n",
        "!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/D32k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained -o D32k.pth\n",
        "!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/D40k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained -o D40k.pth\n",
        "!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/D48k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained -o D48k.pth\n",
        "!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/G32k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained -o G32k.pth\n",
        "!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/G40k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained -o G40k.pth\n",
        "!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/G48k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained -o G48k.pth\n",
        "!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/f0D32k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained -o f0D32k.pth\n",
        "!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/f0D40k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained -o f0D40k.pth\n",
        "!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/f0D48k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained -o f0D48k.pth\n",
        "!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/f0G32k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained -o f0G32k.pth\n",
        "!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/f0G40k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained -o f0G40k.pth\n",
        "!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/f0G48k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained -o f0G48k.pth"
      ],
      "metadata": {
        "id": "UG3XpUwEomUz"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@title 下载人声分离模型\n",
        "!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/uvr5_weights/HP2-人声vocals+非人声instrumentals.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/uvr5_weights -o HP2-人声vocals+非人声instrumentals.pth\n",
        "!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/uvr5_weights/HP5-主旋律人声vocals+其他instrumentals.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/uvr5_weights -o HP5-主旋律人声vocals+其他instrumentals.pth"
      ],
      "metadata": {
        "id": "HugjmZqZRuiF"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@title 下载hubert_base\n",
        "!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/hubert_base.pt -d /content/Retrieval-based-Voice-Conversion-WebUI -o hubert_base.pt"
      ],
      "metadata": {
        "id": "2RCaT9FTR0ej"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@title 挂载谷歌云盘\n",
        "\n",
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "metadata": {
        "id": "jwu07JgqoFON"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@title 从谷歌云盘加载打包好的数据集到/content/dataset\n",
        "\n",
        "#@markdown 数据集位置\n",
        "DATASET = \"/content/drive/MyDrive/dataset/lulu20230327_32k.zip\"  #@param {type:\"string\"}\n",
        "\n",
        "!mkdir -p /content/dataset\n",
        "!unzip -d /content/dataset -B {DATASET}"
      ],
      "metadata": {
        "id": "Mwk7Q0Loqzjx"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@title 重命名数据集中的重名文件\n",
        "!ls -a /content/dataset/\n",
        "!rename 's/(\\w+)\\.(\\w+)~(\\d*)/$1_$3.$2/' /content/dataset/*.*~*"
      ],
      "metadata": {
        "id": "PDlFxWHWEynD"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@title 启动web\n",
        "%cd /content/Retrieval-based-Voice-Conversion-WebUI\n",
        "# %load_ext tensorboard\n",
        "# %tensorboard --logdir /content/Retrieval-based-Voice-Conversion-WebUI/logs\n",
        "!python3 infer-web.py --colab --pycmd python3"
      ],
      "metadata": {
        "id": "7vh6vphDwO0b"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@title 手动将训练后的模型文件备份到谷歌云盘\n",
        "#@markdown 需要自己查看logs文件夹下模型的文件名，手动修改下方命令末尾的文件名\n",
        "\n",
        "#@markdown 模型名\n",
        "MODELNAME = \"lulu\"  #@param {type:\"string\"}\n",
        "#@markdown 模型epoch\n",
        "MODELEPOCH = 9600  #@param {type:\"integer\"}\n",
        "\n",
        "!cp /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/G_{MODELEPOCH}.pth /content/drive/MyDrive/{MODELNAME}_D_{MODELEPOCH}.pth\n",
        "!cp /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/D_{MODELEPOCH}.pth /content/drive/MyDrive/{MODELNAME}_G_{MODELEPOCH}.pth\n",
        "!cp /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/added_*.index /content/drive/MyDrive/\n",
        "!cp /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/total_*.npy /content/drive/MyDrive/\n",
        "\n",
        "!cp /content/Retrieval-based-Voice-Conversion-WebUI/weights/{MODELNAME}.pth /content/drive/MyDrive/{MODELNAME}{MODELEPOCH}.pth"
      ],
      "metadata": {
        "id": "FgJuNeAwx5Y_"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@title 从谷歌云盘恢复pth\n",
        "#@markdown 需要自己查看logs文件夹下模型的文件名，手动修改下方命令末尾的文件名\n",
        "\n",
        "#@markdown 模型名\n",
        "MODELNAME = \"lulu\"  #@param {type:\"string\"}\n",
        "#@markdown 模型epoch\n",
        "MODELEPOCH = 7500  #@param {type:\"integer\"}\n",
        "\n",
        "!mkdir -p /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}\n",
        "\n",
        "!cp /content/drive/MyDrive/{MODELNAME}_D_{MODELEPOCH}.pth /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/G_{MODELEPOCH}.pth\n",
        "!cp /content/drive/MyDrive/{MODELNAME}_G_{MODELEPOCH}.pth /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/D_{MODELEPOCH}.pth\n",
        "!cp /content/drive/MyDrive/*.index /content/\n",
        "!cp /content/drive/MyDrive/*.npy /content/\n",
        "!cp /content/drive/MyDrive/{MODELNAME}{MODELEPOCH}.pth /content/Retrieval-based-Voice-Conversion-WebUI/weights/{MODELNAME}.pth"
      ],
      "metadata": {
        "id": "OVQoLQJXS7WX"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@title 手动预处理（不推荐）\n",
        "#@markdown 模型名\n",
        "MODELNAME = \"lulu\"  #@param {type:\"string\"}\n",
        "#@markdown 采样率\n",
        "BITRATE = 48000  #@param {type:\"integer\"}\n",
        "#@markdown 使用的进程数\n",
        "THREADCOUNT = 8  #@param {type:\"integer\"}\n",
        "\n",
        "!python3 trainset_preprocess_pipeline_print.py /content/dataset {BITRATE} {THREADCOUNT} logs/{MODELNAME} True\n"
      ],
      "metadata": {
        "id": "ZKAyuKb9J6dz"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@title 手动提取特征（不推荐）\n",
        "#@markdown 模型名\n",
        "MODELNAME = \"lulu\"  #@param {type:\"string\"}\n",
        "#@markdown 使用的进程数\n",
        "THREADCOUNT = 8  #@param {type:\"integer\"}\n",
        "#@markdown 音高提取算法\n",
        "ALGO = \"harvest\"  #@param {type:\"string\"}\n",
        "\n",
        "!python3 extract_f0_print.py logs/{MODELNAME} {THREADCOUNT} {ALGO}\n",
        "\n",
        "!python3 extract_feature_print.py cpu 1 0 0 logs/{MODELNAME}\n"
      ],
      "metadata": {
        "id": "CrxJqzAUKmPJ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@title 手动训练（不推荐）\n",
        "#@markdown 模型名\n",
        "MODELNAME = \"lulu\"  #@param {type:\"string\"}\n",
        "#@markdown 使用的GPU\n",
        "USEGPU = \"0\"  #@param {type:\"string\"}\n",
        "#@markdown 批大小\n",
        "BATCHSIZE = 32  #@param {type:\"integer\"}\n",
        "#@markdown 停止的epoch\n",
        "MODELEPOCH = 3200  #@param {type:\"integer\"}\n",
        "#@markdown 保存epoch间隔\n",
        "EPOCHSAVE = 100  #@param {type:\"integer\"}\n",
        "#@markdown 采样率\n",
        "MODELSAMPLE = \"48k\"  #@param {type:\"string\"}\n",
        "#@markdown 是否缓存训练集\n",
        "CACHEDATA = 1  #@param {type:\"integer\"}\n",
        "#@markdown 是否仅保存最新的ckpt文件\n",
        "ONLYLATEST = 0  #@param {type:\"integer\"}\n",
        "\n",
        "!python3 train_nsf_sim_cache_sid_load_pretrain.py -e lulu -sr {MODELSAMPLE} -f0 1 -bs {BATCHSIZE} -g {USEGPU} -te {MODELEPOCH} -se {EPOCHSAVE} -pg pretrained/f0G{MODELSAMPLE}.pth -pd pretrained/f0D{MODELSAMPLE}.pth -l {ONLYLATEST} -c {CACHEDATA}\n"
      ],
      "metadata": {
        "id": "IMLPLKOaKj58"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@title 删除其它pth，只留选中的（慎点，仔细看代码）\n",
        "#@markdown 模型名\n",
        "MODELNAME = \"lulu\"  #@param {type:\"string\"}\n",
        "#@markdown 选中模型epoch\n",
        "MODELEPOCH = 9600  #@param {type:\"integer\"}\n",
        "\n",
        "!echo \"备份选中的模型。。。\"\n",
        "!cp /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/G_{MODELEPOCH}.pth /content/{MODELNAME}_D_{MODELEPOCH}.pth\n",
        "!cp /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/D_{MODELEPOCH}.pth /content/{MODELNAME}_G_{MODELEPOCH}.pth\n",
        "\n",
        "!echo \"正在删除。。。\"\n",
        "!ls /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}\n",
        "!rm /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/*.pth\n",
        "\n",
        "!echo \"恢复选中的模型。。。\"\n",
        "!mv /content/{MODELNAME}_D_{MODELEPOCH}.pth /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/G_{MODELEPOCH}.pth \n",
        "!mv /content/{MODELNAME}_G_{MODELEPOCH}.pth /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/D_{MODELEPOCH}.pth\n",
        "\n",
        "!echo \"删除完成\"\n",
        "!ls /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}"
      ],
      "metadata": {
        "id": "haYA81hySuDl"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@title 清除项目下所有文件，只留选中的模型（慎点，仔细看代码）\n",
        "#@markdown 模型名\n",
        "MODELNAME = \"lulu\"  #@param {type:\"string\"}\n",
        "#@markdown 选中模型epoch\n",
        "MODELEPOCH = 9600  #@param {type:\"integer\"}\n",
        "\n",
        "!echo \"备份选中的模型。。。\"\n",
        "!cp /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/G_{MODELEPOCH}.pth /content/{MODELNAME}_D_{MODELEPOCH}.pth\n",
        "!cp /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/D_{MODELEPOCH}.pth /content/{MODELNAME}_G_{MODELEPOCH}.pth\n",
        "\n",
        "!echo \"正在删除。。。\"\n",
        "!ls /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}\n",
        "!rm -rf /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/*\n",
        "\n",
        "!echo \"恢复选中的模型。。。\"\n",
        "!mv /content/{MODELNAME}_D_{MODELEPOCH}.pth /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/G_{MODELEPOCH}.pth \n",
        "!mv /content/{MODELNAME}_G_{MODELEPOCH}.pth /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/D_{MODELEPOCH}.pth\n",
        "\n",
        "!echo \"删除完成\"\n",
        "!ls /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}"
      ],
      "metadata": {
        "id": "QhSiPTVPoIRh"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}

一键复制编辑原始数据按行查看历史

提交于 2年前 . thanks to RVC-Project ❤

#@title 查看显卡
!nvidia-smi

#@title 安装依赖
!apt-get -y install build-essential python3-dev ffmpeg
!pip3 install --upgrade setuptools wheel
!pip3 install --upgrade pip
!pip3 install faiss-gpu fairseq gradio ffmpeg ffmpeg-python praat-parselmouth pyworld numpy==1.23.5 numba==0.56.4 librosa==0.9.2

#@title 克隆仓库

!git clone --depth=1 -b stable https://github.com/fumiama/Retrieval-based-Voice-Conversion-WebUI
%cd /content/Retrieval-based-Voice-Conversion-WebUI
!mkdir -p pretrained uvr5_weights

#@title 更新仓库（一般无需执行）
!git pull

#@title 安装aria2
!apt -y install -qq aria2

#@title 下载底模
!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/D32k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained -o D32k.pth
!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/D40k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained -o D40k.pth
!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/D48k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained -o D48k.pth
!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/G32k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained -o G32k.pth
!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/G40k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained -o G40k.pth
!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/G48k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained -o G48k.pth
!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/f0D32k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained -o f0D32k.pth
!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/f0D40k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained -o f0D40k.pth
!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/f0D48k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained -o f0D48k.pth
!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/f0G32k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained -o f0G32k.pth
!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/f0G40k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained -o f0G40k.pth
!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/f0G48k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained -o f0G48k.pth

#@title 下载人声分离模型
!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/uvr5_weights/HP2-人声vocals+非人声instrumentals.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/uvr5_weights -o HP2-人声vocals+非人声instrumentals.pth
!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/uvr5_weights/HP5-主旋律人声vocals+其他instrumentals.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/uvr5_weights -o HP5-主旋律人声vocals+其他instrumentals.pth

#@title 下载hubert_base
!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/hubert_base.pt -d /content/Retrieval-based-Voice-Conversion-WebUI -o hubert_base.pt

#@title 挂载谷歌云盘

from google.colab import drive
drive.mount('/content/drive')

#@title 从谷歌云盘加载打包好的数据集到/content/dataset

#@markdown 数据集位置
DATASET = "/content/drive/MyDrive/dataset/lulu20230327_32k.zip"  #@param {type:"string"}

!mkdir -p /content/dataset
!unzip -d /content/dataset -B {DATASET}

#@title 重命名数据集中的重名文件
!ls -a /content/dataset/
!rename 's/(\w+)\.(\w+)~(\d*)/$1_$3.$2/' /content/dataset/*.*~*

#@title 启动web
%cd /content/Retrieval-based-Voice-Conversion-WebUI
# %load_ext tensorboard
# %tensorboard --logdir /content/Retrieval-based-Voice-Conversion-WebUI/logs
!python3 infer-web.py --colab --pycmd python3

#@title 手动将训练后的模型文件备份到谷歌云盘
#@markdown 需要自己查看logs文件夹下模型的文件名，手动修改下方命令末尾的文件名

#@markdown 模型名
MODELNAME = "lulu"  #@param {type:"string"}
#@markdown 模型epoch
MODELEPOCH = 9600  #@param {type:"integer"}

!cp /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/G_{MODELEPOCH}.pth /content/drive/MyDrive/{MODELNAME}_D_{MODELEPOCH}.pth
!cp /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/D_{MODELEPOCH}.pth /content/drive/MyDrive/{MODELNAME}_G_{MODELEPOCH}.pth
!cp /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/added_*.index /content/drive/MyDrive/
!cp /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/total_*.npy /content/drive/MyDrive/

!cp /content/Retrieval-based-Voice-Conversion-WebUI/weights/{MODELNAME}.pth /content/drive/MyDrive/{MODELNAME}{MODELEPOCH}.pth

#@title 从谷歌云盘恢复pth
#@markdown 需要自己查看logs文件夹下模型的文件名，手动修改下方命令末尾的文件名

#@markdown 模型名
MODELNAME = "lulu"  #@param {type:"string"}
#@markdown 模型epoch
MODELEPOCH = 7500  #@param {type:"integer"}

!mkdir -p /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}

!cp /content/drive/MyDrive/{MODELNAME}_D_{MODELEPOCH}.pth /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/G_{MODELEPOCH}.pth
!cp /content/drive/MyDrive/{MODELNAME}_G_{MODELEPOCH}.pth /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/D_{MODELEPOCH}.pth
!cp /content/drive/MyDrive/*.index /content/
!cp /content/drive/MyDrive/*.npy /content/
!cp /content/drive/MyDrive/{MODELNAME}{MODELEPOCH}.pth /content/Retrieval-based-Voice-Conversion-WebUI/weights/{MODELNAME}.pth

#@title 手动预处理（不推荐）
#@markdown 模型名
MODELNAME = "lulu"  #@param {type:"string"}
#@markdown 采样率
BITRATE = 48000  #@param {type:"integer"}
#@markdown 使用的进程数
THREADCOUNT = 8  #@param {type:"integer"}

!python3 trainset_preprocess_pipeline_print.py /content/dataset {BITRATE} {THREADCOUNT} logs/{MODELNAME} True

#@title 手动提取特征（不推荐）
#@markdown 模型名
MODELNAME = "lulu"  #@param {type:"string"}
#@markdown 使用的进程数
THREADCOUNT = 8  #@param {type:"integer"}
#@markdown 音高提取算法
ALGO = "harvest"  #@param {type:"string"}

!python3 extract_f0_print.py logs/{MODELNAME} {THREADCOUNT} {ALGO}

!python3 extract_feature_print.py cpu 1 0 0 logs/{MODELNAME}

#@title 手动训练（不推荐）
#@markdown 模型名
MODELNAME = "lulu"  #@param {type:"string"}
#@markdown 使用的GPU
USEGPU = "0"  #@param {type:"string"}
#@markdown 批大小
BATCHSIZE = 32  #@param {type:"integer"}
#@markdown 停止的epoch
MODELEPOCH = 3200  #@param {type:"integer"}
#@markdown 保存epoch间隔
EPOCHSAVE = 100  #@param {type:"integer"}
#@markdown 采样率
MODELSAMPLE = "48k"  #@param {type:"string"}
#@markdown 是否缓存训练集
CACHEDATA = 1  #@param {type:"integer"}
#@markdown 是否仅保存最新的ckpt文件
ONLYLATEST = 0  #@param {type:"integer"}

!python3 train_nsf_sim_cache_sid_load_pretrain.py -e lulu -sr {MODELSAMPLE} -f0 1 -bs {BATCHSIZE} -g {USEGPU} -te {MODELEPOCH} -se {EPOCHSAVE} -pg pretrained/f0G{MODELSAMPLE}.pth -pd pretrained/f0D{MODELSAMPLE}.pth -l {ONLYLATEST} -c {CACHEDATA}

#@title 删除其它pth，只留选中的（慎点，仔细看代码）
#@markdown 模型名
MODELNAME = "lulu"  #@param {type:"string"}
#@markdown 选中模型epoch
MODELEPOCH = 9600  #@param {type:"integer"}

!echo "备份选中的模型。。。"
!cp /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/G_{MODELEPOCH}.pth /content/{MODELNAME}_D_{MODELEPOCH}.pth
!cp /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/D_{MODELEPOCH}.pth /content/{MODELNAME}_G_{MODELEPOCH}.pth

!echo "正在删除。。。"
!ls /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}
!rm /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/*.pth

!echo "恢复选中的模型。。。"
!mv /content/{MODELNAME}_D_{MODELEPOCH}.pth /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/G_{MODELEPOCH}.pth 
!mv /content/{MODELNAME}_G_{MODELEPOCH}.pth /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/D_{MODELEPOCH}.pth

!echo "删除完成"
!ls /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}

#@title 清除项目下所有文件，只留选中的模型（慎点，仔细看代码）
#@markdown 模型名
MODELNAME = "lulu"  #@param {type:"string"}
#@markdown 选中模型epoch
MODELEPOCH = 9600  #@param {type:"integer"}

!echo "备份选中的模型。。。"
!cp /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/G_{MODELEPOCH}.pth /content/{MODELNAME}_D_{MODELEPOCH}.pth
!cp /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/D_{MODELEPOCH}.pth /content/{MODELNAME}_G_{MODELEPOCH}.pth

!echo "正在删除。。。"
!ls /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}
!rm -rf /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/*

!echo "恢复选中的模型。。。"
!mv /content/{MODELNAME}_D_{MODELEPOCH}.pth /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/G_{MODELEPOCH}.pth 
!mv /content/{MODELNAME}_G_{MODELEPOCH}.pth /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/D_{MODELEPOCH}.pth

!echo "删除完成"
!ls /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}

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