{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "gpuType": "T4",
      "authorship_tag": "ABX9TyP9xA/YzXZ1hfHjb0pJbiMF",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/Blane187/rvc-tts/blob/main/rvc_tts.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "RVC TTS BASED ON [litagin02/rvc-tts-webui](https://github.com/litagin02/rvc-tts-webui)"
      ],
      "metadata": {
        "id": "DKHM0u_hwK5d"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "id": "PXkFSrJ4R4QK"
      },
      "outputs": [],
      "source": [
        "\n",
        "#@title clone\n",
        "\n",
        "server = \"https://github.com/Blane187/rvc-tts\"\n",
        "\n",
        "tts = \"rvc-tts\"\n",
        "\n",
        "!git clone $server\n",
        "\n",
        "%cd $tts"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "#@title install requirements\n",
        "\n",
        "!pip install -r requirements.txt --quiet\n",
        "!pip install aria2 --quiet"
      ],
      "metadata": {
        "cellView": "form",
        "id": "inqwVlPpSzqD"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "#@title download model\n",
        "\n",
        "!python download.py"
      ],
      "metadata": {
        "cellView": "form",
        "id": "ccAEpKyGTfzt"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Model Download Function\n",
        "\n",
        "import os\n",
        "import zipfile\n",
        "import shutil\n",
        "import urllib.request\n",
        "\n",
        "BASE_DIR = os.getcwd()\n",
        "rvc_models_dir = os.path.join(BASE_DIR, 'weights')\n",
        "\n",
        "def extract_zip(extraction_folder, zip_name):\n",
        "    os.makedirs(extraction_folder)\n",
        "    with zipfile.ZipFile(zip_name, 'r') as zip_ref:\n",
        "        zip_ref.extractall(extraction_folder)\n",
        "    os.remove(zip_name)\n",
        "\n",
        "    index_filepath, model_filepath = None, None\n",
        "    for root, dirs, files in os.walk(extraction_folder):\n",
        "        for name in files:\n",
        "            if name.endswith('.index') and os.stat(os.path.join(root, name)).st_size > 1024 * 100:\n",
        "                index_filepath = os.path.join(root, name)\n",
        "\n",
        "            if name.endswith('.pth') and os.stat(os.path.join(root, name)).st_size > 1024 * 1024 * 40:\n",
        "                model_filepath = os.path.join(root, name)\n",
        "\n",
        "    if not model_filepath:\n",
        "        raise Exception(f'No .pth model file was found in the extracted zip. Please check {extraction_folder}.')\n",
        "\n",
        "    # move model and index file to extraction folder\n",
        "    os.rename(model_filepath, os.path.join(extraction_folder, os.path.basename(model_filepath)))\n",
        "    if index_filepath:\n",
        "        os.rename(index_filepath, os.path.join(extraction_folder, os.path.basename(index_filepath)))\n",
        "\n",
        "    # remove any unnecessary nested folders\n",
        "    for filepath in os.listdir(extraction_folder):\n",
        "        if os.path.isdir(os.path.join(extraction_folder, filepath)):\n",
        "            shutil.rmtree(os.path.join(extraction_folder, filepath))\n",
        "\n",
        "def download_online_model(url, dir_name):\n",
        "    try:\n",
        "        print(f'[~] Downloading voice model with name {dir_name}...')\n",
        "        zip_name = url.split('/')[-1]\n",
        "        extraction_folder = os.path.join(rvc_models_dir, dir_name)\n",
        "        if os.path.exists(extraction_folder):\n",
        "            raise Exception(f'Voice model directory {dir_name} already exists! Choose a different name for your voice model.')\n",
        "\n",
        "        if 'pixeldrain.com' in url:\n",
        "            url = f'https://pixeldrain.com/api/file/{zip_name}'\n",
        "\n",
        "        urllib.request.urlretrieve(url, zip_name)\n",
        "\n",
        "        print('[~] Extracting zip...')\n",
        "        extract_zip(extraction_folder, zip_name)\n",
        "        print(f'[+] {dir_name} Model successfully downloaded 😆')\n",
        "\n",
        "    except Exception as e:\n",
        "        raise Exception(str(e))\n",
        "\n",
        "url = \"https://pixeldrain.com/u/3tJmABXA\" # @param {type:\"string\"}\n",
        "dir_name = \"Gura\" # @param {type:\"string\"}\n",
        "\n",
        "download_online_model(url, dir_name)"
      ],
      "metadata": {
        "cellView": "form",
        "id": "8EO0QzQ5VdTQ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "\n",
        "#@title run\n",
        "!python app.py"
      ],
      "metadata": {
        "cellView": "form",
        "id": "fwh0j3VJUbNp"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}