Deepfake_end_to_end_tortoise_wav2lip_Colab.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "reqK2fYU8RMa"
      },
      "source": [
        "Automatic DeepFake Creation (Tortoise voice cloning + wav2lip)\n",
        "\n",
        "Note: A video is required. If an audio is also provided, the voice will be cloned from the audio.\n",
        "\n",
        "# **The video should have a face looking at all times to the camera.**\n",
        "\n",
        "## **Video (and audio) file should be in Google drive in a folder named 'deepfake'. No other files should exist there**\n",
        "\n",
        "wav2lip code taken from https://github.com/snehitvaddi/Deepfake-using-Wave2Lip"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3jsyyKrp8osG",
        "outputId": "6bb3fa29-7c77-4072-f72c-00440c1a5411"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Mounted at /content/gdrive\n"
          ]
        }
      ],
      "source": [
        "#@title Upload video.mp4 (video to overlay voice) & voice.mp3 (voice to clone) files - Should be mp3 and mp4, having any name\n",
        "from google.colab import drive\n",
        "drive.mount('/content/gdrive')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "iCKcGNEhlP8N",
        "outputId": "eaedcc3d-5eef-4954-d071-0d1e1d33326d"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "/content/gdrive/MyDrive/deepfake\n"
          ]
        }
      ],
      "source": [
        "cd gdrive/MyDrive/deepfake"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "id": "YD5EdXykqXXo"
      },
      "outputs": [],
      "source": [
        "base_path='/content/gdrive/MyDrive/deepfake' #Specify path of video/audio"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ODXQ2Hx3RLWv",
        "outputId": "20d02990-9c07-4c4f-8a59-dc370b282450"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
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            "\u001b[?25h  Building wheel for encodec (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Building wheel for bnnumerizer (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Building wheel for bnunicodenormalizer (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
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            "  Building wheel for gruut-ipa (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Building wheel for gruut_lang_de (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Building wheel for gruut_lang_en (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Building wheel for gruut_lang_es (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Building wheel for gruut_lang_fr (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Building wheel for gruut (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "chex 0.1.86 requires numpy>=1.24.1, but you have numpy 1.22.0 which is incompatible.\n",
            "cudf-cu12 24.4.1 requires numpy<2.0a0,>=1.23, but you have numpy 1.22.0 which is incompatible.\n",
            "cudf-cu12 24.4.1 requires pandas<2.2.2dev0,>=2.0, but you have pandas 1.5.3 which is incompatible.\n",
            "google-colab 1.0.0 requires pandas==2.0.3, but you have pandas 1.5.3 which is incompatible.\n",
            "pandas-stubs 2.0.3.230814 requires numpy>=1.25.0; python_version >= \"3.9\", but you have numpy 1.22.0 which is incompatible.\n",
            "plotnine 0.12.4 requires numpy>=1.23.0, but you have numpy 1.22.0 which is incompatible.\n",
            "pywavelets 1.6.0 requires numpy<3,>=1.22.4, but you have numpy 1.22.0 which is incompatible.\n",
            "rmm-cu12 24.4.0 requires numpy<2.0a0,>=1.23, but you have numpy 1.22.0 which is incompatible.\n",
            "statsmodels 0.14.2 requires numpy>=1.22.3, but you have numpy 1.22.0 which is incompatible.\n",
            "tensorflow 2.15.0 requires numpy<2.0.0,>=1.23.5, but you have numpy 1.22.0 which is incompatible.\u001b[0m\u001b[31m\n",
            "\u001b[0m"
          ]
        }
      ],
      "source": [
        "#@title Install TTS, pydub to create folders with audio chunks, and moviepy to modify duration of audio/video\n",
        "!pip install -q pydub==0.25.1 TTS==0.22.0 moviepy==1.0.3"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "id": "9NAT2EgsCx_o"
      },
      "outputs": [],
      "source": [
        "#@title English text that we want to read with the cloned voice - This will be inserted in the video too\n",
        "#Text prompt should be separated with '|' every one to two sentences (every ~20secs it takes to read it).\n",
        "text_to_read=\"\"\"Joining two modalities results in a surprising increase in generalization!\n",
        "What would happen if we combined them all? |\"\"\""
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "id": "wntESyuu_jcm"
      },
      "outputs": [],
      "source": [
        "#@title Rename audio and video files to be used below\n",
        "#Prompt: the user selects and uploads to google colab one audio and one video file. Rename the audio file to 'input_voice.mp3' and the video to 'input_video.mp4'\n",
        "import os\n",
        "\n",
        "# Loop over files in the directory\n",
        "for file in os.listdir(os.getcwd()):\n",
        "\n",
        "      filename = os.path.join(base_path, file)\n",
        "\n",
        "      if filename.endswith('.mp3'):\n",
        "          new_filename = 'input_voice.mp3'\n",
        "          os.rename(filename, new_filename)\n",
        "      if filename.endswith('.mp4'):\n",
        "          new_filename = 'video_full.mp4'\n",
        "          os.rename(filename, new_filename)\n",
        "\n",
        "#If only video is provided:\n",
        "from moviepy.editor import VideoFileClip\n",
        "\n",
        "def extract_audio(input_video, output_audio):\n",
        "    video = VideoFileClip(input_video)\n",
        "    audio = video.audio\n",
        "    audio.write_audiofile(output_audio)\n",
        "\n",
        "# Provide the input video file path and desired output audio file path\n",
        "input_video = 'video_full.mp4'\n",
        "output_audio = 'input_voice.mp3'\n",
        "\n",
        "#Decide if voice will be cloned from video or audio\n",
        "mp3_check=0\n",
        "for file in os.listdir(os.getcwd()):\n",
        "      file_path =  os.path.join(base_path, file)\n",
        "      if '.mp3' in file_path:\n",
        "        mp3_check=1\n",
        "\n",
        "if mp3_check==0:\n",
        "  print(\"Voice will be cloned from video\")\n",
        "  extract_audio(input_video, output_audio)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "OekWB8DRAUsh",
        "outputId": "3f9663d7-d754-44b2-eb38-21caa67f5a81"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "121 clips saved in '/content/gdrive/MyDrive/deepfake/voice'.\n"
          ]
        }
      ],
      "source": [
        "#@title Create folder with 10 secs chunks of audio to be used as input in Tortoise\n",
        "from pydub import AudioSegment\n",
        "\n",
        "def split_audio_to_clips(audio_file, output_dir, clip_length=10000, sample_rate=22050):\n",
        "    # Load the audio file\n",
        "    audio = AudioSegment.from_mp3(audio_file)\n",
        "\n",
        "    # Create the output directory if it doesn't exist\n",
        "    if not os.path.exists(output_dir):\n",
        "        os.makedirs(output_dir)\n",
        "\n",
        "    # Calculate the total number of clips\n",
        "    num_clips = len(audio) // clip_length\n",
        "\n",
        "    # Split the audio into clips and save them as WAV files\n",
        "    for i in range(num_clips):\n",
        "        start_time = i * clip_length\n",
        "        end_time = start_time + clip_length\n",
        "        clip = audio[start_time:end_time]\n",
        "\n",
        "        # Set the sample width to 2 bytes for floating-point format\n",
        "        clip = clip.set_sample_width(2)\n",
        "\n",
        "        # Set the sample rate to 22050 Hz\n",
        "        clip = clip.set_frame_rate(sample_rate)\n",
        "\n",
        "        # Save the clip as a WAV file\n",
        "        clip.export(os.path.join(output_dir, f\"{i+1}.wav\"), format=\"wav\")\n",
        "\n",
        "    print(f\"{num_clips} clips saved in '{output_dir}'.\")\n",
        "\n",
        "if __name__ == \"__main__\":\n",
        "\n",
        "    # Replace 'input_audio.mp3' with the name of your MP3 file\n",
        "    input_audio_file = base_path+'/input_voice.mp3'\n",
        "\n",
        "    # Replace 'voices' with the desired subdirectory name\n",
        "    subdirectory_name = base_path+'/voice'\n",
        "\n",
        "    split_audio_to_clips(input_audio_file, subdirectory_name)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zYRGVrEe75f9",
        "outputId": "2bfb8c1d-ab23-4064-f6c0-3a523190c3c8"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            " > Downloading model to /root/.local/share/tts/tts_models--en--multi-dataset--tortoise-v2\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
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          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            " > Model's license - apache 2.0\n",
            " > Check https://choosealicense.com/licenses/apache-2.0/ for more info.\n",
            " > Using model: tortoise\n"
          ]
        }
      ],
      "source": [
        "#@title Download and run TTS tortoise model\n",
        "from TTS.api import TTS\n",
        "tts = TTS(\"tts_models/en/multi-dataset/tortoise-v2\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "IPxbWjtILaPR",
        "outputId": "9258ef20-1307-49af-99e4-566129321d40"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
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            "  Downloading scipy-1.13.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (38.6 MB)\n",
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            "\u001b[?25hCollecting numpy<2.3,>=1.22.4 (from scipy)\n",
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            "\u001b[?25hInstalling collected packages: numpy, scipy\n",
            "  Attempting uninstall: numpy\n",
            "    Found existing installation: numpy 1.22.0\n",
            "    Uninstalling numpy-1.22.0:\n",
            "      Successfully uninstalled numpy-1.22.0\n",
            "  Attempting uninstall: scipy\n",
            "    Found existing installation: scipy 1.11.4\n",
            "    Uninstalling scipy-1.11.4:\n",
            "      Successfully uninstalled scipy-1.11.4\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "tts 0.22.0 requires numpy==1.22.0; python_version <= \"3.10\", but you have numpy 1.26.4 which is incompatible.\n",
            "cudf-cu12 24.4.1 requires pandas<2.2.2dev0,>=2.0, but you have pandas 1.5.3 which is incompatible.\u001b[0m\u001b[31m\n",
            "\u001b[0mSuccessfully installed numpy-1.26.4 scipy-1.13.0\n",
            "Cloning into 'tortoise-tts'...\n",
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            "/content/gdrive/MyDrive/deepfake/tortoise-tts\n",
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            "Collecting librosa (from -r requirements.txt (line 10))\n",
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            "\u001b[?25hCollecting resampy>=0.2.2 (from librosa->-r requirements.txt (line 10))\n",
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            "Building wheels for collected packages: numba, progressbar, ffmpeg, llvmlite\n",
            "  \u001b[1;31merror\u001b[0m: \u001b[1msubprocess-exited-with-error\u001b[0m\n",
            "  \n",
            "  \u001b[31m×\u001b[0m \u001b[32mpython setup.py bdist_wheel\u001b[0m did not run successfully.\n",
            "  \u001b[31m│\u001b[0m exit code: \u001b[1;36m1\u001b[0m\n",
            "  \u001b[31m╰─>\u001b[0m See above for output.\n",
            "  \n",
            "  \u001b[1;35mnote\u001b[0m: This error originates from a subprocess, and is likely not a problem with pip.\n",
            "  Building wheel for numba (setup.py) ... \u001b[?25lerror\n",
            "\u001b[31m  ERROR: Failed building wheel for numba\u001b[0m\u001b[31m\n",
            "\u001b[0m\u001b[?25h  Running setup.py clean for numba\n",
            "  Building wheel for progressbar (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for progressbar: filename=progressbar-2.5-py3-none-any.whl size=12067 sha256=b7bd9d04882d965a1dffc29f1c200aa6f8b07a07670f1dfc1795270ce95daefb\n",
            "  Stored in directory: /root/.cache/pip/wheels/cd/17/e5/765d1a3112ff3978f70223502f6047e06c43a24d7c5f8ff95b\n",
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            "  Created wheel for ffmpeg: filename=ffmpeg-1.4-py3-none-any.whl size=6082 sha256=dd3b4aec79a85eb6a146c65b56fd218dcaa3ebc9d756190ae98841b6b995d8a7\n",
            "  Stored in directory: /root/.cache/pip/wheels/8e/7a/69/cd6aeb83b126a7f04cbe7c9d929028dc52a6e7d525ff56003a\n",
            "  \u001b[1;31merror\u001b[0m: \u001b[1msubprocess-exited-with-error\u001b[0m\n",
            "  \n",
            "  \u001b[31m×\u001b[0m \u001b[32mpython setup.py bdist_wheel\u001b[0m did not run successfully.\n",
            "  \u001b[31m│\u001b[0m exit code: \u001b[1;36m1\u001b[0m\n",
            "  \u001b[31m╰─>\u001b[0m See above for output.\n",
            "  \n",
            "  \u001b[1;35mnote\u001b[0m: This error originates from a subprocess, and is likely not a problem with pip.\n",
            "  Building wheel for llvmlite (setup.py) ... \u001b[?25lerror\n",
            "\u001b[31m  ERROR: Failed building wheel for llvmlite\u001b[0m\u001b[31m\n",
            "\u001b[0m\u001b[?25h  Running setup.py clean for llvmlite\n",
            "Successfully built progressbar ffmpeg\n",
            "Failed to build numba llvmlite\n",
            "\u001b[31mERROR: Could not build wheels for numba, llvmlite, which is required to install pyproject.toml-based projects\u001b[0m\u001b[31m\n",
            "\u001b[0mCollecting transformers==4.19.0\n",
            "  Downloading transformers-4.19.0-py3-none-any.whl (4.2 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m4.2/4.2 MB\u001b[0m \u001b[31m49.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting einops==0.5.0\n",
            "  Downloading einops-0.5.0-py3-none-any.whl (36 kB)\n",
            "Collecting rotary_embedding_torch==0.1.5\n",
            "  Downloading rotary_embedding_torch-0.1.5-py3-none-any.whl (4.1 kB)\n",
            "Collecting unidecode==1.3.5\n",
            "  Downloading Unidecode-1.3.5-py3-none-any.whl (236 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m236.5/236.5 kB\u001b[0m \u001b[31m31.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from transformers==4.19.0) (3.14.0)\n",
            "Requirement already satisfied: huggingface-hub<1.0,>=0.1.0 in /usr/local/lib/python3.10/dist-packages (from transformers==4.19.0) (0.20.3)\n",
            "Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.10/dist-packages (from transformers==4.19.0) (1.26.4)\n",
            "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from transformers==4.19.0) (24.0)\n",
            "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.10/dist-packages (from transformers==4.19.0) (6.0.1)\n",
            "Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.10/dist-packages (from transformers==4.19.0) (2023.12.25)\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from transformers==4.19.0) (2.31.0)\n",
            "Collecting tokenizers!=0.11.3,<0.13,>=0.11.1 (from transformers==4.19.0)\n",
            "  Downloading tokenizers-0.12.1-cp310-cp310-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (6.6 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m6.6/6.6 MB\u001b[0m \u001b[31m84.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: tqdm>=4.27 in /usr/local/lib/python3.10/dist-packages (from transformers==4.19.0) (4.66.4)\n",
            "Requirement already satisfied: torch>=1.6 in /usr/local/lib/python3.10/dist-packages (from rotary_embedding_torch==0.1.5) (2.2.1+cu121)\n",
            "Requirement already satisfied: fsspec>=2023.5.0 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub<1.0,>=0.1.0->transformers==4.19.0) (2023.6.0)\n",
            "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub<1.0,>=0.1.0->transformers==4.19.0) (4.11.0)\n",
            "Requirement already satisfied: sympy in /usr/local/lib/python3.10/dist-packages (from torch>=1.6->rotary_embedding_torch==0.1.5) (1.12)\n",
            "Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (from torch>=1.6->rotary_embedding_torch==0.1.5) (2.8.8)\n",
            "Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from torch>=1.6->rotary_embedding_torch==0.1.5) (3.1.4)\n",
            "Requirement already satisfied: nvidia-cuda-nvrtc-cu12==12.1.105 in /usr/local/lib/python3.10/dist-packages (from torch>=1.6->rotary_embedding_torch==0.1.5) (12.1.105)\n",
            "Requirement already satisfied: nvidia-cuda-runtime-cu12==12.1.105 in /usr/local/lib/python3.10/dist-packages (from torch>=1.6->rotary_embedding_torch==0.1.5) (12.1.105)\n",
            "Requirement already satisfied: nvidia-cuda-cupti-cu12==12.1.105 in /usr/local/lib/python3.10/dist-packages (from torch>=1.6->rotary_embedding_torch==0.1.5) (12.1.105)\n",
            "Requirement already satisfied: nvidia-cudnn-cu12==8.9.2.26 in /usr/local/lib/python3.10/dist-packages (from torch>=1.6->rotary_embedding_torch==0.1.5) (8.9.2.26)\n",
            "Requirement already satisfied: nvidia-cublas-cu12==12.1.3.1 in /usr/local/lib/python3.10/dist-packages (from torch>=1.6->rotary_embedding_torch==0.1.5) (12.1.3.1)\n",
            "Requirement already satisfied: nvidia-cufft-cu12==11.0.2.54 in /usr/local/lib/python3.10/dist-packages (from torch>=1.6->rotary_embedding_torch==0.1.5) (11.0.2.54)\n",
            "Requirement already satisfied: nvidia-curand-cu12==10.3.2.106 in /usr/local/lib/python3.10/dist-packages (from torch>=1.6->rotary_embedding_torch==0.1.5) (10.3.2.106)\n",
            "Requirement already satisfied: nvidia-cusolver-cu12==11.4.5.107 in /usr/local/lib/python3.10/dist-packages (from torch>=1.6->rotary_embedding_torch==0.1.5) (11.4.5.107)\n",
            "Requirement already satisfied: nvidia-cusparse-cu12==12.1.0.106 in /usr/local/lib/python3.10/dist-packages (from torch>=1.6->rotary_embedding_torch==0.1.5) (12.1.0.106)\n",
            "Requirement already satisfied: nvidia-nccl-cu12==2.19.3 in /usr/local/lib/python3.10/dist-packages (from torch>=1.6->rotary_embedding_torch==0.1.5) (2.19.3)\n",
            "Requirement already satisfied: nvidia-nvtx-cu12==12.1.105 in /usr/local/lib/python3.10/dist-packages (from torch>=1.6->rotary_embedding_torch==0.1.5) (12.1.105)\n",
            "Requirement already satisfied: triton==2.2.0 in /usr/local/lib/python3.10/dist-packages (from torch>=1.6->rotary_embedding_torch==0.1.5) (2.2.0)\n",
            "Requirement already satisfied: nvidia-nvjitlink-cu12 in /usr/local/lib/python3.10/dist-packages (from nvidia-cusolver-cu12==11.4.5.107->torch>=1.6->rotary_embedding_torch==0.1.5) (12.4.127)\n",
            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->transformers==4.19.0) (3.3.2)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->transformers==4.19.0) (3.7)\n",
            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->transformers==4.19.0) (2.0.7)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->transformers==4.19.0) (2024.2.2)\n",
            "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch>=1.6->rotary_embedding_torch==0.1.5) (2.1.5)\n",
            "Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.10/dist-packages (from sympy->torch>=1.6->rotary_embedding_torch==0.1.5) (1.3.0)\n",
            "\u001b[33mWARNING: The candidate selected for download or install is a yanked version: 'unidecode' candidate (version 1.3.5 at https://files.pythonhosted.org/packages/7c/bb/a1cea9ce56434cdb59cb4c8b7bf91b190011b7000fb0a12b44fa0a3daa86/Unidecode-1.3.5-py3-none-any.whl (from https://pypi.org/simple/unidecode/) (requires-python:>=3.5))\n",
            "Reason for being yanked: wrong version of the code was released in the .whl package\u001b[0m\u001b[33m\n",
            "\u001b[0mInstalling collected packages: tokenizers, unidecode, einops, transformers, rotary_embedding_torch\n",
            "  Attempting uninstall: tokenizers\n",
            "    Found existing installation: tokenizers 0.19.1\n",
            "    Uninstalling tokenizers-0.19.1:\n",
            "      Successfully uninstalled tokenizers-0.19.1\n",
            "  Attempting uninstall: unidecode\n",
            "    Found existing installation: Unidecode 1.3.8\n",
            "    Uninstalling Unidecode-1.3.8:\n",
            "      Successfully uninstalled Unidecode-1.3.8\n",
            "  Attempting uninstall: einops\n",
            "    Found existing installation: einops 0.8.0\n",
            "    Uninstalling einops-0.8.0:\n",
            "      Successfully uninstalled einops-0.8.0\n",
            "  Attempting uninstall: transformers\n",
            "    Found existing installation: transformers 4.40.2\n",
            "    Uninstalling transformers-4.40.2:\n",
            "      Successfully uninstalled transformers-4.40.2\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "tts 0.22.0 requires einops>=0.6.0, but you have einops 0.5.0 which is incompatible.\n",
            "tts 0.22.0 requires numpy==1.22.0; python_version <= \"3.10\", but you have numpy 1.26.4 which is incompatible.\n",
            "tts 0.22.0 requires transformers>=4.33.0, but you have transformers 4.19.0 which is incompatible.\u001b[0m\u001b[31m\n",
            "\u001b[0mSuccessfully installed einops-0.5.0 rotary_embedding_torch-0.1.5 tokenizers-0.12.1 transformers-4.19.0 unidecode-1.3.5\n"
          ]
        },
        {
          "data": {
            "application/vnd.colab-display-data+json": {
              "id": "c8f6f566ad3442649c7a7da0e47ad75e",
              "pip_warning": {
                "packages": [
                  "tokenizers",
                  "transformers"
                ]
              }
            }
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "running install\n",
            "/usr/local/lib/python3.10/dist-packages/setuptools/_distutils/cmd.py:66: SetuptoolsDeprecationWarning: setup.py install is deprecated.\n",
            "!!\n",
            "\n",
            "        ********************************************************************************\n",
            "        Please avoid running ``setup.py`` directly.\n",
            "        Instead, use pypa/build, pypa/installer, pypa/build or\n",
            "        other standards-based tools.\n",
            "\n",
            "        See https://blog.ganssle.io/articles/2021/10/setup-py-deprecated.html for details.\n",
            "        ********************************************************************************\n",
            "\n",
            "!!\n",
            "  self.initialize_options()\n",
            "/usr/local/lib/python3.10/dist-packages/setuptools/_distutils/cmd.py:66: EasyInstallDeprecationWarning: easy_install command is deprecated.\n",
            "!!\n",
            "\n",
            "        ********************************************************************************\n",
            "        Please avoid running ``setup.py`` and ``easy_install``.\n",
            "        Instead, use pypa/build, pypa/installer, pypa/build or\n",
            "        other standards-based tools.\n",
            "\n",
            "        See https://github.com/pypa/setuptools/issues/917 for details.\n",
            "        ********************************************************************************\n",
            "\n",
            "!!\n",
            "  self.initialize_options()\n",
            "running bdist_egg\n",
            "running egg_info\n",
            "creating TorToiSe.egg-info\n",
            "writing TorToiSe.egg-info/PKG-INFO\n",
            "writing dependency_links to TorToiSe.egg-info/dependency_links.txt\n",
            "writing requirements to TorToiSe.egg-info/requires.txt\n",
            "writing top-level names to TorToiSe.egg-info/top_level.txt\n",
            "writing manifest file 'TorToiSe.egg-info/SOURCES.txt'\n",
            "reading manifest file 'TorToiSe.egg-info/SOURCES.txt'\n",
            "adding license file 'LICENSE'\n",
            "writing manifest file 'TorToiSe.egg-info/SOURCES.txt'\n",
            "installing library code to build/bdist.linux-x86_64/egg\n",
            "running install_lib\n",
            "running build_py\n",
            "creating build\n",
            "creating build/lib\n",
            "creating build/lib/tortoise\n",
            "copying tortoise/__init__.py -> build/lib/tortoise\n",
            "copying tortoise/api.py -> build/lib/tortoise\n",
            "copying tortoise/do_tts.py -> build/lib/tortoise\n",
            "copying tortoise/eval.py -> build/lib/tortoise\n",
            "copying tortoise/get_conditioning_latents.py -> build/lib/tortoise\n",
            "copying tortoise/is_this_from_tortoise.py -> build/lib/tortoise\n",
            "copying tortoise/read.py -> build/lib/tortoise\n",
            "creating build/lib/tortoise/models\n",
            "copying tortoise/models/__init__.py -> build/lib/tortoise/models\n",
            "copying tortoise/models/arch_util.py -> build/lib/tortoise/models\n",
            "copying tortoise/models/autoregressive.py -> build/lib/tortoise/models\n",
            "copying tortoise/models/classifier.py -> build/lib/tortoise/models\n",
            "copying tortoise/models/clvp.py -> build/lib/tortoise/models\n",
            "copying tortoise/models/cvvp.py -> build/lib/tortoise/models\n",
            "copying tortoise/models/diffusion_decoder.py -> build/lib/tortoise/models\n",
            "copying tortoise/models/random_latent_generator.py -> build/lib/tortoise/models\n",
            "copying tortoise/models/transformer.py -> build/lib/tortoise/models\n",
            "copying tortoise/models/vocoder.py -> build/lib/tortoise/models\n",
            "copying tortoise/models/xtransformers.py -> build/lib/tortoise/models\n",
            "creating build/lib/tortoise/utils\n",
            "copying tortoise/utils/__init__.py -> build/lib/tortoise/utils\n",
            "copying tortoise/utils/audio.py -> build/lib/tortoise/utils\n",
            "copying tortoise/utils/diffusion.py -> build/lib/tortoise/utils\n",
            "copying tortoise/utils/samples_generator.py -> build/lib/tortoise/utils\n",
            "copying tortoise/utils/stft.py -> build/lib/tortoise/utils\n",
            "copying tortoise/utils/text.py -> build/lib/tortoise/utils\n",
            "copying tortoise/utils/tokenizer.py -> build/lib/tortoise/utils\n",
            "copying tortoise/utils/typical_sampling.py -> build/lib/tortoise/utils\n",
            "copying tortoise/utils/wav2vec_alignment.py -> build/lib/tortoise/utils\n",
            "creating build/bdist.linux-x86_64\n",
            "creating build/bdist.linux-x86_64/egg\n",
            "creating build/bdist.linux-x86_64/egg/tortoise\n",
            "copying build/lib/tortoise/__init__.py -> build/bdist.linux-x86_64/egg/tortoise\n",
            "copying build/lib/tortoise/api.py -> build/bdist.linux-x86_64/egg/tortoise\n",
            "copying build/lib/tortoise/do_tts.py -> build/bdist.linux-x86_64/egg/tortoise\n",
            "copying build/lib/tortoise/eval.py -> build/bdist.linux-x86_64/egg/tortoise\n",
            "copying build/lib/tortoise/get_conditioning_latents.py -> build/bdist.linux-x86_64/egg/tortoise\n",
            "copying build/lib/tortoise/is_this_from_tortoise.py -> build/bdist.linux-x86_64/egg/tortoise\n",
            "copying build/lib/tortoise/read.py -> build/bdist.linux-x86_64/egg/tortoise\n",
            "creating build/bdist.linux-x86_64/egg/tortoise/models\n",
            "copying build/lib/tortoise/models/__init__.py -> build/bdist.linux-x86_64/egg/tortoise/models\n",
            "copying build/lib/tortoise/models/arch_util.py -> build/bdist.linux-x86_64/egg/tortoise/models\n",
            "copying build/lib/tortoise/models/autoregressive.py -> build/bdist.linux-x86_64/egg/tortoise/models\n",
            "copying build/lib/tortoise/models/classifier.py -> build/bdist.linux-x86_64/egg/tortoise/models\n",
            "copying build/lib/tortoise/models/clvp.py -> build/bdist.linux-x86_64/egg/tortoise/models\n",
            "copying build/lib/tortoise/models/cvvp.py -> build/bdist.linux-x86_64/egg/tortoise/models\n",
            "copying build/lib/tortoise/models/diffusion_decoder.py -> build/bdist.linux-x86_64/egg/tortoise/models\n",
            "copying build/lib/tortoise/models/random_latent_generator.py -> build/bdist.linux-x86_64/egg/tortoise/models\n",
            "copying build/lib/tortoise/models/transformer.py -> build/bdist.linux-x86_64/egg/tortoise/models\n",
            "copying build/lib/tortoise/models/vocoder.py -> build/bdist.linux-x86_64/egg/tortoise/models\n",
            "copying build/lib/tortoise/models/xtransformers.py -> build/bdist.linux-x86_64/egg/tortoise/models\n",
            "creating build/bdist.linux-x86_64/egg/tortoise/utils\n",
            "copying build/lib/tortoise/utils/__init__.py -> build/bdist.linux-x86_64/egg/tortoise/utils\n",
            "copying build/lib/tortoise/utils/audio.py -> build/bdist.linux-x86_64/egg/tortoise/utils\n",
            "copying build/lib/tortoise/utils/diffusion.py -> build/bdist.linux-x86_64/egg/tortoise/utils\n",
            "copying build/lib/tortoise/utils/samples_generator.py -> build/bdist.linux-x86_64/egg/tortoise/utils\n",
            "copying build/lib/tortoise/utils/stft.py -> build/bdist.linux-x86_64/egg/tortoise/utils\n",
            "copying build/lib/tortoise/utils/text.py -> build/bdist.linux-x86_64/egg/tortoise/utils\n",
            "copying build/lib/tortoise/utils/tokenizer.py -> build/bdist.linux-x86_64/egg/tortoise/utils\n",
            "copying build/lib/tortoise/utils/typical_sampling.py -> build/bdist.linux-x86_64/egg/tortoise/utils\n",
            "copying build/lib/tortoise/utils/wav2vec_alignment.py -> build/bdist.linux-x86_64/egg/tortoise/utils\n",
            "byte-compiling build/bdist.linux-x86_64/egg/tortoise/__init__.py to __init__.cpython-310.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/tortoise/api.py to api.cpython-310.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/tortoise/do_tts.py to do_tts.cpython-310.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/tortoise/eval.py to eval.cpython-310.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/tortoise/get_conditioning_latents.py to get_conditioning_latents.cpython-310.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/tortoise/is_this_from_tortoise.py to is_this_from_tortoise.cpython-310.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/tortoise/read.py to read.cpython-310.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/tortoise/models/__init__.py to __init__.cpython-310.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/tortoise/models/arch_util.py to arch_util.cpython-310.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/tortoise/models/autoregressive.py to autoregressive.cpython-310.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/tortoise/models/classifier.py to classifier.cpython-310.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/tortoise/models/clvp.py to clvp.cpython-310.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/tortoise/models/cvvp.py to cvvp.cpython-310.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/tortoise/models/diffusion_decoder.py to diffusion_decoder.cpython-310.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/tortoise/models/random_latent_generator.py to random_latent_generator.cpython-310.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/tortoise/models/transformer.py to transformer.cpython-310.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/tortoise/models/vocoder.py to vocoder.cpython-310.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/tortoise/models/xtransformers.py to xtransformers.cpython-310.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/tortoise/utils/__init__.py to __init__.cpython-310.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/tortoise/utils/audio.py to audio.cpython-310.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/tortoise/utils/diffusion.py to diffusion.cpython-310.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/tortoise/utils/samples_generator.py to samples_generator.cpython-310.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/tortoise/utils/stft.py to stft.cpython-310.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/tortoise/utils/text.py to text.cpython-310.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/tortoise/utils/tokenizer.py to tokenizer.cpython-310.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/tortoise/utils/typical_sampling.py to typical_sampling.cpython-310.pyc\n",
            "byte-compiling build/bdist.linux-x86_64/egg/tortoise/utils/wav2vec_alignment.py to wav2vec_alignment.cpython-310.pyc\n",
            "creating build/bdist.linux-x86_64/egg/EGG-INFO\n",
            "copying TorToiSe.egg-info/PKG-INFO -> build/bdist.linux-x86_64/egg/EGG-INFO\n",
            "copying TorToiSe.egg-info/SOURCES.txt -> build/bdist.linux-x86_64/egg/EGG-INFO\n",
            "copying TorToiSe.egg-info/dependency_links.txt -> build/bdist.linux-x86_64/egg/EGG-INFO\n",
            "copying TorToiSe.egg-info/requires.txt -> build/bdist.linux-x86_64/egg/EGG-INFO\n",
            "copying TorToiSe.egg-info/top_level.txt -> build/bdist.linux-x86_64/egg/EGG-INFO\n",
            "zip_safe flag not set; analyzing archive contents...\n",
            "creating dist\n",
            "creating 'dist/TorToiSe-2.3.0-py3.10.egg' and adding 'build/bdist.linux-x86_64/egg' to it\n",
            "removing 'build/bdist.linux-x86_64/egg' (and everything under it)\n",
            "Processing TorToiSe-2.3.0-py3.10.egg\n",
            "Copying TorToiSe-2.3.0-py3.10.egg to /usr/local/lib/python3.10/dist-packages\n",
            "Adding TorToiSe 2.3.0 to easy-install.pth file\n",
            "\n",
            "Installed /usr/local/lib/python3.10/dist-packages/TorToiSe-2.3.0-py3.10.egg\n",
            "Processing dependencies for TorToiSe==2.3.0\n",
            "Searching for progressbar\n",
            "Reading https://pypi.org/simple/progressbar/\n",
            "Downloading https://files.pythonhosted.org/packages/a3/a6/b8e451f6cff1c99b4747a2f7235aa904d2d49e8e1464e0b798272aa84358/progressbar-2.5.tar.gz#sha256=5d81cb529da2e223b53962afd6c8ca0f05c6670e40309a7219eacc36af9b6c63\n",
            "Best match: progressbar 2.5\n",
            "Processing progressbar-2.5.tar.gz\n",
            "Writing /tmp/easy_install-d3ol0f0f/progressbar-2.5/setup.cfg\n",
            "Running progressbar-2.5/setup.py -q bdist_egg --dist-dir /tmp/easy_install-d3ol0f0f/progressbar-2.5/egg-dist-tmp-4go8_2yh\n",
            "/usr/local/lib/python3.10/dist-packages/setuptools/_distutils/cmd.py:66: SetuptoolsDeprecationWarning: setup.py install is deprecated.\n",
            "!!\n",
            "\n",
            "        ********************************************************************************\n",
            "        Please avoid running ``setup.py`` directly.\n",
            "        Instead, use pypa/build, pypa/installer, pypa/build or\n",
            "        other standards-based tools.\n",
            "\n",
            "        See https://blog.ganssle.io/articles/2021/10/setup-py-deprecated.html for details.\n",
            "        ********************************************************************************\n",
            "\n",
            "!!\n",
            "  self.initialize_options()\n",
            "zip_safe flag not set; analyzing archive contents...\n",
            "Adding progressbar 2.5 to easy-install.pth file\n",
            "\n",
            "Installed /usr/local/lib/python3.10/dist-packages/progressbar-2.5-py3.10.egg\n",
            "Searching for tokenizers==0.12.1\n",
            "Best match: tokenizers 0.12.1\n",
            "Adding tokenizers 0.12.1 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for transformers==4.19.0\n",
            "Best match: transformers 4.19.0\n",
            "Adding transformers 4.19.0 to easy-install.pth file\n",
            "Installing transformers-cli script to /usr/local/bin\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for librosa==0.10.0\n",
            "Best match: librosa 0.10.0\n",
            "Adding librosa 0.10.0 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for scipy==1.13.0\n",
            "Best match: scipy 1.13.0\n",
            "Adding scipy 1.13.0 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for Unidecode==1.3.5\n",
            "Best match: Unidecode 1.3.5\n",
            "Adding Unidecode 1.3.5 to easy-install.pth file\n",
            "Installing unidecode script to /usr/local/bin\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for einops==0.5.0\n",
            "Best match: einops 0.5.0\n",
            "Adding einops 0.5.0 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for inflect==7.0.0\n",
            "Best match: inflect 7.0.0\n",
            "Adding inflect 7.0.0 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for rotary-embedding-torch==0.1.5\n",
            "Best match: rotary-embedding-torch 0.1.5\n",
            "Adding rotary-embedding-torch 0.1.5 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for tqdm==4.66.4\n",
            "Best match: tqdm 4.66.4\n",
            "Adding tqdm 4.66.4 to easy-install.pth file\n",
            "Installing tqdm script to /usr/local/bin\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for requests==2.31.0\n",
            "Best match: requests 2.31.0\n",
            "Adding requests 2.31.0 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for regex==2023.12.25\n",
            "Best match: regex 2023.12.25\n",
            "Adding regex 2023.12.25 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for PyYAML==6.0.1\n",
            "Best match: PyYAML 6.0.1\n",
            "Adding PyYAML 6.0.1 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for packaging==24.0\n",
            "Best match: packaging 24.0\n",
            "Adding packaging 24.0 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for numpy==1.26.4\n",
            "Best match: numpy 1.26.4\n",
            "Adding numpy 1.26.4 to easy-install.pth file\n",
            "Installing f2py script to /usr/local/bin\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for huggingface-hub==0.20.3\n",
            "Best match: huggingface-hub 0.20.3\n",
            "Adding huggingface-hub 0.20.3 to easy-install.pth file\n",
            "Installing huggingface-cli script to /usr/local/bin\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for filelock==3.14.0\n",
            "Best match: filelock 3.14.0\n",
            "Adding filelock 3.14.0 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for msgpack==1.0.8\n",
            "Best match: msgpack 1.0.8\n",
            "Adding msgpack 1.0.8 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for lazy-loader==0.4\n",
            "Best match: lazy-loader 0.4\n",
            "Adding lazy-loader 0.4 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for typing-extensions==4.11.0\n",
            "Best match: typing-extensions 4.11.0\n",
            "Adding typing-extensions 4.11.0 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for soxr==0.3.7\n",
            "Best match: soxr 0.3.7\n",
            "Adding soxr 0.3.7 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for pooch==1.8.1\n",
            "Best match: pooch 1.8.1\n",
            "Adding pooch 1.8.1 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for soundfile==0.12.1\n",
            "Best match: soundfile 0.12.1\n",
            "Adding soundfile 0.12.1 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for numba==0.58.1\n",
            "Best match: numba 0.58.1\n",
            "Adding numba 0.58.1 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for decorator==4.4.2\n",
            "Best match: decorator 4.4.2\n",
            "Adding decorator 4.4.2 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for joblib==1.4.2\n",
            "Best match: joblib 1.4.2\n",
            "Adding joblib 1.4.2 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for scikit-learn==1.4.2\n",
            "Best match: scikit-learn 1.4.2\n",
            "Adding scikit-learn 1.4.2 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for audioread==3.0.1\n",
            "Best match: audioread 3.0.1\n",
            "Adding audioread 3.0.1 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for pydantic==2.7.1\n",
            "Best match: pydantic 2.7.1\n",
            "Adding pydantic 2.7.1 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for torch==2.2.1+cu121\n",
            "Best match: torch 2.2.1+cu121\n",
            "Adding torch 2.2.1+cu121 to easy-install.pth file\n",
            "Installing convert-caffe2-to-onnx script to /usr/local/bin\n",
            "Installing convert-onnx-to-caffe2 script to /usr/local/bin\n",
            "Installing torchrun script to /usr/local/bin\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for certifi==2024.2.2\n",
            "Best match: certifi 2024.2.2\n",
            "Adding certifi 2024.2.2 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for urllib3==2.0.7\n",
            "Best match: urllib3 2.0.7\n",
            "Adding urllib3 2.0.7 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for idna==3.7\n",
            "Best match: idna 3.7\n",
            "Adding idna 3.7 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for charset-normalizer==3.3.2\n",
            "Best match: charset-normalizer 3.3.2\n",
            "Adding charset-normalizer 3.3.2 to easy-install.pth file\n",
            "Installing normalizer script to /usr/local/bin\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for fsspec==2023.6.0\n",
            "Best match: fsspec 2023.6.0\n",
            "Adding fsspec 2023.6.0 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for platformdirs==4.2.1\n",
            "Best match: platformdirs 4.2.1\n",
            "Adding platformdirs 4.2.1 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for cffi==1.16.0\n",
            "Best match: cffi 1.16.0\n",
            "Adding cffi 1.16.0 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for llvmlite==0.41.1\n",
            "Best match: llvmlite 0.41.1\n",
            "Adding llvmlite 0.41.1 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for threadpoolctl==3.5.0\n",
            "Best match: threadpoolctl 3.5.0\n",
            "Adding threadpoolctl 3.5.0 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for pydantic-core==2.18.2\n",
            "Best match: pydantic-core 2.18.2\n",
            "Adding pydantic-core 2.18.2 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for annotated-types==0.6.0\n",
            "Best match: annotated-types 0.6.0\n",
            "Adding annotated-types 0.6.0 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for triton==2.2.0\n",
            "Best match: triton 2.2.0\n",
            "Adding triton 2.2.0 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for nvidia-nvtx-cu12==12.1.105\n",
            "Best match: nvidia-nvtx-cu12 12.1.105\n",
            "Adding nvidia-nvtx-cu12 12.1.105 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for nvidia-nccl-cu12==2.19.3\n",
            "Best match: nvidia-nccl-cu12 2.19.3\n",
            "Adding nvidia-nccl-cu12 2.19.3 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for nvidia-cusparse-cu12==12.1.0.106\n",
            "Best match: nvidia-cusparse-cu12 12.1.0.106\n",
            "Adding nvidia-cusparse-cu12 12.1.0.106 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for nvidia-cusolver-cu12==11.4.5.107\n",
            "Best match: nvidia-cusolver-cu12 11.4.5.107\n",
            "Adding nvidia-cusolver-cu12 11.4.5.107 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for nvidia-curand-cu12==10.3.2.106\n",
            "Best match: nvidia-curand-cu12 10.3.2.106\n",
            "Adding nvidia-curand-cu12 10.3.2.106 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for nvidia-cufft-cu12==11.0.2.54\n",
            "Best match: nvidia-cufft-cu12 11.0.2.54\n",
            "Adding nvidia-cufft-cu12 11.0.2.54 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for nvidia-cublas-cu12==12.1.3.1\n",
            "Best match: nvidia-cublas-cu12 12.1.3.1\n",
            "Adding nvidia-cublas-cu12 12.1.3.1 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for nvidia-cudnn-cu12==8.9.2.26\n",
            "Best match: nvidia-cudnn-cu12 8.9.2.26\n",
            "Adding nvidia-cudnn-cu12 8.9.2.26 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for nvidia-cuda-cupti-cu12==12.1.105\n",
            "Best match: nvidia-cuda-cupti-cu12 12.1.105\n",
            "Adding nvidia-cuda-cupti-cu12 12.1.105 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for nvidia-cuda-runtime-cu12==12.1.105\n",
            "Best match: nvidia-cuda-runtime-cu12 12.1.105\n",
            "Adding nvidia-cuda-runtime-cu12 12.1.105 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for nvidia-cuda-nvrtc-cu12==12.1.105\n",
            "Best match: nvidia-cuda-nvrtc-cu12 12.1.105\n",
            "Adding nvidia-cuda-nvrtc-cu12 12.1.105 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for jinja2==3.1.4\n",
            "Best match: jinja2 3.1.4\n",
            "Adding jinja2 3.1.4 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for networkx==2.8.8\n",
            "Best match: networkx 2.8.8\n",
            "Adding networkx 2.8.8 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for sympy==1.12\n",
            "Best match: sympy 1.12\n",
            "Adding sympy 1.12 to easy-install.pth file\n",
            "Installing isympy script to /usr/local/bin\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for pycparser==2.22\n",
            "Best match: pycparser 2.22\n",
            "Adding pycparser 2.22 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for nvidia-nvjitlink-cu12==12.4.127\n",
            "Best match: nvidia-nvjitlink-cu12 12.4.127\n",
            "Adding nvidia-nvjitlink-cu12 12.4.127 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for MarkupSafe==2.1.5\n",
            "Best match: MarkupSafe 2.1.5\n",
            "Adding MarkupSafe 2.1.5 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Searching for mpmath==1.3.0\n",
            "Best match: mpmath 1.3.0\n",
            "Adding mpmath 1.3.0 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.10/dist-packages\n",
            "Finished processing dependencies for TorToiSe==2.3.0\n"
          ]
        }
      ],
      "source": [
        "#@title Install tortoise original repository to be used to merge cloned audio pieces together\n",
        "!pip3 install -U scipy\n",
        "\n",
        "!git clone https://github.com/jnordberg/tortoise-tts.git\n",
        "%cd tortoise-tts\n",
        "!pip3 install -r requirements.txt\n",
        "!pip3 install transformers==4.19.0 einops==0.5.0 rotary_embedding_torch==0.1.5 unidecode==1.3.5\n",
        "!python3 setup.py install"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MtRwfD9gLv83",
        "outputId": "57107d70-3829-4ba3-8f03-36a4a8a03ed0"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Found the '|' character in your text, which I will use as a cue for where to split it up. If this was notyour intent, please remove all '|' characters from the input.\n"
          ]
        }
      ],
      "source": [
        "from tortoise.utils.text import split_and_recombine_text\n",
        "from time import time\n",
        "\n",
        "# Process text\n",
        "text = text_to_read\n",
        "if '|' in text:\n",
        "    print(\"Found the '|' character in your text, which I will use as a cue for where to split it up. If this was not\"\n",
        "          \"your intent, please remove all '|' characters from the input.\")\n",
        "    texts = text.split('|')\n",
        "else:\n",
        "    texts = split_and_recombine_text(text) #If only one piece of text (<20secs), convert it to list"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "tUOhLGPELgpG",
        "outputId": "2ea691d5-2e05-4ed2-aa89-07c3e2d3cf15"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "/content/gdrive/MyDrive/deepfake\n"
          ]
        }
      ],
      "source": [
        "cd .."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "#Tortoise Fastest Inference from script (~2min per 20secs of audio in Colab)\n",
        "#Can also be downloaded from https://huggingface.co/jbetker/tortoise-tts-v2/tree/main\n",
        "import torch\n",
        "import torchaudio\n",
        "\n",
        "from TTS.tts.configs.tortoise_config import TortoiseConfig\n",
        "from TTS.tts.models.tortoise import Tortoise\n",
        "import IPython\n",
        "import gc\n",
        "\n",
        "config = TortoiseConfig()\n",
        "model = Tortoise.init_from_config(config)\n",
        "model.load_checkpoint(config, checkpoint_dir=\"/root/.local/share/tts/tts_models--en--multi-dataset--tortoise-v2\", eval=True) #Deepspeed doesn't work\n",
        "model.cuda()\n",
        "\n",
        "all_parts = []\n",
        "for j, text in enumerate(texts): #Combine individuals pieces of text by processing sound one piece at a time (around 20secs each)\n",
        "  # cloning a speaker\n",
        "  output_dict = model.synthesize(text, config, speaker_id=\"voice\", voice_dirs=base_path)\n",
        "\n",
        "  #Save result\n",
        "  torchaudio.save(\"tortoise_v2_script_\"+str(j)+\".wav\", torch.tensor(output_dict[\"wav\"]).squeeze(0), 24000)\n",
        "  all_parts.append(torch.tensor(output_dict[\"wav\"]).squeeze(0))\n",
        "  del output_dict\n",
        "\n",
        "  # Perform garbage collection\n",
        "  gc.collect()\n",
        "\n",
        "torchaudio.save('combined.wav', torch.cat(all_parts, dim=-1), 24000)\n",
        "IPython.display.Audio('combined.wav')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "hsrktP_DZUl3"
      },
      "source": [
        "Clean memory so that we can have a bit longer text to read"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {
        "id": "Xjt6pDpvMVV5"
      },
      "outputs": [],
      "source": [
        "del all_parts"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 14,
      "metadata": {
        "id": "PdGcmAfNpVPz"
      },
      "outputs": [],
      "source": [
        "for name in dir():\n",
        "    if not name.startswith('_'):\n",
        "        del globals()[name]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 15,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nd3X1kF-MTu-",
        "outputId": "082187d8-e47b-40c2-c3e7-48003ab5e598"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "21"
            ]
          },
          "execution_count": 15,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "import gc\n",
        "# Perform garbage collection\n",
        "gc.collect()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "from google.colab import files\n",
        "files.download('/content/gdrive/MyDrive/deepfake/combined.wav')\n",
        "#Individual pieces can also be found in this folder"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 16,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "a4o_-0yd-GRC",
        "outputId": "865bb295-5e82-44a7-c1db-557ae5126dd0"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "100%|██████████| 4.40k/4.40k [13:18<00:00, 5.51iB/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Moviepy - Building video input_video.mp4.\n",
            "MoviePy - Writing audio in input_videoTEMP_MPY_wvf_snd.mp3\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n",
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          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "MoviePy - Done.\n",
            "Moviepy - Writing video input_video.mp4\n",
            "\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
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          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Moviepy - Done !\n",
            "Moviepy - video ready input_video.mp4\n"
          ]
        }
      ],
      "source": [
        "#@title Confirm that audio same length as video. If not, keep the smallest one and cut the other (or cut them both to 20secs). This is needed for wav2lip to work\n",
        "#ChatGPT Prompt: Create python code that compares an audio.wav with a video.mp4 files and if the duration of one is bigger than the other,\n",
        "# it cuts the largest one to be the same duration as the smallest. If any of them is bigger than 20secs then raise an error\n",
        "\n",
        "#Needed to avoid errors with encoding\n",
        "import locale\n",
        "locale.getpreferredencoding = lambda: \"UTF-8\"\n",
        "\n",
        "from moviepy.editor import VideoFileClip, AudioFileClip\n",
        "import os\n",
        "\n",
        "def compare_audio_video_duration(audio_file, video_file):\n",
        "    audio = AudioFileClip(audio_file)\n",
        "    video = VideoFileClip(video_file)\n",
        "\n",
        "    audio_duration = audio.duration\n",
        "    video_duration = video.duration\n",
        "\n",
        "    # Either the video or audio should be <20 secs. If any of these is larger than that, it will be cut to the duration of the other or to 20secs.\n",
        "    # Might work for up to 30secs, but not guaranteed. If only video is provided, it will keep only the first 20 secs of it.\n",
        "\n",
        "    # if audio_duration > 20 and video_duration > 20:\n",
        "    #     video = video.subclip(0, 20)\n",
        "    #     video.write_videofile('input_video.mp4')\n",
        "    #     audio = audio.subclip(0, 20)\n",
        "    #     audio.write_audiofile('input_audio.wav')\n",
        "\n",
        "    if audio_duration != video_duration:\n",
        "        min_duration = min(audio_duration, video_duration)\n",
        "        if min_duration == audio_duration:\n",
        "            video = video.subclip(0, min_duration)\n",
        "            video.write_videofile('input_video.mp4')\n",
        "            os.rename(audio_file,'input_audio.wav')\n",
        "        else:\n",
        "            audio = audio.subclip(0, min_duration)\n",
        "            audio.write_audiofile('input_audio.wav')\n",
        "            os.rename(video_file,'input_video.mp4')\n",
        "\n",
        "    audio.close()\n",
        "    video.close()\n",
        "\n",
        "# Example usage\n",
        "compare_audio_video_duration(\"combined.wav\", \"video_full.mp4\") #input_voice.mp3"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dT9AQwdf8sJK"
      },
      "source": [
        "\n",
        "\n",
        "---\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 18,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hGEz5MihKSdY",
        "outputId": "f6105d71-fdcc-40b1-fb5e-1bcc2d7cf603"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "/content\n"
          ]
        }
      ],
      "source": [
        "cd /content"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Qgo-oaI3JU2u",
        "outputId": "73ca675a-61f2-48c8-ab1c-29d635ff687a"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "Done\n"
          ]
        }
      ],
      "source": [
        "#@title <h1>Install Wav2Lip</h1>\n",
        "#@markdown * Install dependencies\n",
        "#@markdown * Download models\n",
        "# !rm -rf /content/sample_data\n",
        "# !mkdir /content/sample_data\n",
        "\n",
        "!git clone https://github.com/zabique/Wav2Lip\n",
        "\n",
        "#download the pretrained model\n",
        "!wget 'https://iiitaphyd-my.sharepoint.com/personal/radrabha_m_research_iiit_ac_in/_layouts/15/download.aspx?share=EdjI7bZlgApMqsVoEUUXpLsBxqXbn5z8VTmoxp55YNDcIA' -O '/content/Wav2Lip/checkpoints/wav2lip_gan.pth'\n",
        "!wget 'https://iiitaphyd-my.sharepoint.com/:u:/g/personal/radrabha_m_research_iiit_ac_in/Eb3LEzbfuKlJiR600lQWRxgBIY27JZg80f7V9jtMfbNDaQ?e=TBFBVW' -O /content/Wav2Lip/checkpoints/wav2lip.pth\n",
        "!pip install https://raw.githubusercontent.com/AwaleSajil/ghc/master/ghc-1.0-py3-none-any.whl\n",
        "\n",
        "# !pip uninstall tensorflow tensorflow-gpu\n",
        "!cd Wav2Lip && pip install -r requirements.txt\n",
        "\n",
        "#download pretrained model for face detection\n",
        "!wget \"https://www.adrianbulat.com/downloads/python-fan/s3fd-619a316812.pth\" -O \"/content/Wav2Lip/face_detection/detection/sfd/s3fd.pth\"\n",
        "\n",
        "!pip install -q youtube-dl\n",
        "!pip install ffmpeg-python\n",
        "from IPython.display import clear_output\n",
        "clear_output()\n",
        "print(\"\\nDone\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vzokJMO19IyY"
      },
      "source": [
        "\n",
        "\n",
        "---\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "RgjaWJFs8B38"
      },
      "source": [
        "- Below implementation needs both audio and video to be of same length. Only specific extensions work (mp4 and wav)\n",
        "- Target face in the input_video.mp4, must be \"detectable\" in ALL videoframes (So no black or blurry frames etc)\n",
        "- wav2lip does not like very long and high res clips (1080p/30seconds recommended)\n",
        "- 'Wav2Lip' model gives highly accurate lip-sync compared to 'Wav2Lip + GAN' but with inferior visual quality compared to the latter"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vBvt_c2jdebP"
      },
      "source": [
        "Below is needed to fix an error in loading - Not added in the beginning due to conflict in dependencies"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JLVZhHvL7GMo",
        "outputId": "3b2b26ae-127b-46b3-e913-6aae540ac825"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Requirement already satisfied: librosa==0.9.1 in /usr/local/lib/python3.10/dist-packages (0.9.1)\n",
            "Requirement already satisfied: audioread>=2.1.5 in /usr/local/lib/python3.10/dist-packages (from librosa==0.9.1) (3.0.1)\n",
            "Requirement already satisfied: numpy>=1.17.0 in /usr/local/lib/python3.10/dist-packages (from librosa==0.9.1) (1.26.4)\n",
            "Requirement already satisfied: scipy>=1.2.0 in /usr/local/lib/python3.10/dist-packages (from librosa==0.9.1) (1.13.0)\n",
            "Requirement already satisfied: scikit-learn>=0.19.1 in /usr/local/lib/python3.10/dist-packages (from librosa==0.9.1) (1.4.2)\n",
            "Requirement already satisfied: joblib>=0.14 in /usr/local/lib/python3.10/dist-packages (from librosa==0.9.1) (1.4.2)\n",
            "Requirement already satisfied: decorator>=4.0.10 in /usr/local/lib/python3.10/dist-packages (from librosa==0.9.1) (4.4.2)\n",
            "Requirement already satisfied: resampy>=0.2.2 in /usr/local/lib/python3.10/dist-packages (from librosa==0.9.1) (0.4.3)\n",
            "Requirement already satisfied: numba>=0.45.1 in /usr/local/lib/python3.10/dist-packages (from librosa==0.9.1) (0.58.1)\n",
            "Requirement already satisfied: soundfile>=0.10.2 in /usr/local/lib/python3.10/dist-packages (from librosa==0.9.1) (0.12.1)\n",
            "Requirement already satisfied: pooch>=1.0 in /usr/local/lib/python3.10/dist-packages (from librosa==0.9.1) (1.8.1)\n",
            "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from librosa==0.9.1) (24.0)\n",
            "Requirement already satisfied: llvmlite<0.42,>=0.41.0dev0 in /usr/local/lib/python3.10/dist-packages (from numba>=0.45.1->librosa==0.9.1) (0.41.1)\n",
            "Requirement already satisfied: platformdirs>=2.5.0 in /usr/local/lib/python3.10/dist-packages (from pooch>=1.0->librosa==0.9.1) (4.2.1)\n",
            "Requirement already satisfied: requests>=2.19.0 in /usr/local/lib/python3.10/dist-packages (from pooch>=1.0->librosa==0.9.1) (2.31.0)\n",
            "Requirement already satisfied: threadpoolctl>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from scikit-learn>=0.19.1->librosa==0.9.1) (3.5.0)\n",
            "Requirement already satisfied: cffi>=1.0 in /usr/local/lib/python3.10/dist-packages (from soundfile>=0.10.2->librosa==0.9.1) (1.16.0)\n",
            "Requirement already satisfied: pycparser in /usr/local/lib/python3.10/dist-packages (from cffi>=1.0->soundfile>=0.10.2->librosa==0.9.1) (2.22)\n",
            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests>=2.19.0->pooch>=1.0->librosa==0.9.1) (3.3.2)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests>=2.19.0->pooch>=1.0->librosa==0.9.1) (3.7)\n",
            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests>=2.19.0->pooch>=1.0->librosa==0.9.1) (2.0.7)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests>=2.19.0->pooch>=1.0->librosa==0.9.1) (2024.2.2)\n"
          ]
        }
      ],
      "source": [
        "!pip install librosa==0.9.1"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "RIgm4QcAUL1k"
      },
      "outputs": [],
      "source": [
        "# Clear all user-defined variables except built-in ones\n",
        "for name in dir():\n",
        "    if not name.startswith('_'):\n",
        "        del globals()[name]\n",
        "\n",
        "# Perform garbage collection to free up memory\n",
        "import gc\n",
        "gc.collect()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jR5utmDMcSZY",
        "outputId": "8eed276a-5449-4546-cb3e-86a4e24c97f2"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Using cuda for inference.\n",
            "Reading video frames...\n",
            "Number of frames available for inference: 1130\n",
            "/content/Wav2Lip/audio.py:100: FutureWarning: Pass sr=16000, n_fft=800 as keyword args. From version 0.10 passing these as positional arguments will result in an error\n",
            "  return librosa.filters.mel(hp.sample_rate, hp.n_fft, n_mels=hp.num_mels,\n",
            "(80, 3013)\n",
            "Length of mel chunks: 1126\n",
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            "Load checkpoint from: checkpoints/wav2lip_gan.pth\n",
            "Model loaded\n",
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            "ffmpeg version 4.4.2-0ubuntu0.22.04.1 Copyright (c) 2000-2021 the FFmpeg developers\n",
            "  built with gcc 11 (Ubuntu 11.2.0-19ubuntu1)\n",
            "  configuration: --prefix=/usr --extra-version=0ubuntu0.22.04.1 --toolchain=hardened --libdir=/usr/lib/x86_64-linux-gnu --incdir=/usr/include/x86_64-linux-gnu --arch=amd64 --enable-gpl --disable-stripping --enable-gnutls --enable-ladspa --enable-libaom --enable-libass --enable-libbluray --enable-libbs2b --enable-libcaca --enable-libcdio --enable-libcodec2 --enable-libdav1d --enable-libflite --enable-libfontconfig --enable-libfreetype --enable-libfribidi --enable-libgme --enable-libgsm --enable-libjack --enable-libmp3lame --enable-libmysofa --enable-libopenjpeg --enable-libopenmpt --enable-libopus --enable-libpulse --enable-librabbitmq --enable-librubberband --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libspeex --enable-libsrt --enable-libssh --enable-libtheora --enable-libtwolame --enable-libvidstab --enable-libvorbis --enable-libvpx --enable-libwebp --enable-libx265 --enable-libxml2 --enable-libxvid --enable-libzimg --enable-libzmq --enable-libzvbi --enable-lv2 --enable-omx --enable-openal --enable-opencl --enable-opengl --enable-sdl2 --enable-pocketsphinx --enable-librsvg --enable-libmfx --enable-libdc1394 --enable-libdrm --enable-libiec61883 --enable-chromaprint --enable-frei0r --enable-libx264 --enable-shared\n",
            "  libavutil      56. 70.100 / 56. 70.100\n",
            "  libavcodec     58.134.100 / 58.134.100\n",
            "  libavformat    58. 76.100 / 58. 76.100\n",
            "  libavdevice    58. 13.100 / 58. 13.100\n",
            "  libavfilter     7.110.100 /  7.110.100\n",
            "  libswscale      5.  9.100 /  5.  9.100\n",
            "  libswresample   3.  9.100 /  3.  9.100\n",
            "  libpostproc    55.  9.100 / 55.  9.100\n",
            "\u001b[0;33mGuessed Channel Layout for Input Stream #0.0 : mono\n",
            "\u001b[0mInput #0, wav, from '/content/gdrive/MyDrive/deepfake/input_audio.wav':\n",
            "  Metadata:\n",
            "    encoder         : Lavf58.76.100\n",
            "  Duration: 00:00:37.65, bitrate: 384 kb/s\n",
            "  Stream #0:0: Audio: pcm_s16le ([1][0][0][0] / 0x0001), 24000 Hz, mono, s16, 384 kb/s\n",
            "Input #1, avi, from 'temp/result.avi':\n",
            "  Metadata:\n",
            "    software        : Lavf59.27.100\n",
            "  Duration: 00:00:37.53, start: 0.000000, bitrate: 1399 kb/s\n",
            "  Stream #1:0: Video: mpeg4 (Simple Profile) (DIVX / 0x58564944), yuv420p, 960x540 [SAR 1:1 DAR 16:9], 1393 kb/s, 30 fps, 30 tbr, 30 tbn, 30 tbc\n",
            "Stream mapping:\n",
            "  Stream #1:0 -> #0:0 (mpeg4 (native) -> h264 (libx264))\n",
            "  Stream #0:0 -> #0:1 (pcm_s16le (native) -> aac (native))\n",
            "Press [q] to stop, [?] for help\n",
            "\u001b[1;36m[libx264 @ 0x5b3adecf8100] \u001b[0m\u001b[0;33m-qscale is ignored, -crf is recommended.\n",
            "\u001b[0m\u001b[1;36m[libx264 @ 0x5b3adecf8100] \u001b[0musing SAR=1/1\n",
            "\u001b[1;36m[libx264 @ 0x5b3adecf8100] \u001b[0musing cpu capabilities: MMX2 SSE2Fast SSSE3 SSE4.2 AVX FMA3 BMI2 AVX2 AVX512\n",
            "\u001b[1;36m[libx264 @ 0x5b3adecf8100] \u001b[0mprofile High, level 3.1, 4:2:0, 8-bit\n",
            "\u001b[1;36m[libx264 @ 0x5b3adecf8100] \u001b[0m264 - core 163 r3060 5db6aa6 - H.264/MPEG-4 AVC codec - Copyleft 2003-2021 - http://www.videolan.org/x264.html - options: cabac=1 ref=3 deblock=1:0:0 analyse=0x3:0x113 me=hex subme=7 psy=1 psy_rd=1.00:0.00 mixed_ref=1 me_range=16 chroma_me=1 trellis=1 8x8dct=1 cqm=0 deadzone=21,11 fast_pskip=1 chroma_qp_offset=-2 threads=3 lookahead_threads=1 sliced_threads=0 nr=0 decimate=1 interlaced=0 bluray_compat=0 constrained_intra=0 bframes=3 b_pyramid=2 b_adapt=1 b_bias=0 direct=1 weightb=1 open_gop=0 weightp=2 keyint=250 keyint_min=25 scenecut=40 intra_refresh=0 rc_lookahead=40 rc=crf mbtree=1 crf=23.0 qcomp=0.60 qpmin=0 qpmax=69 qpstep=4 ip_ratio=1.40 aq=1:1.00\n",
            "Output #0, mp4, to 'results/result_voice.mp4':\n",
            "  Metadata:\n",
            "    encoder         : Lavf58.76.100\n",
            "  Stream #0:0: Video: h264 (avc1 / 0x31637661), yuv420p(progressive), 960x540 [SAR 1:1 DAR 16:9], q=2-31, 30 fps, 15360 tbn\n",
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            "      encoder         : Lavc58.134.100 libx264\n",
            "    Side data:\n",
            "      cpb: bitrate max/min/avg: 0/0/0 buffer size: 0 vbv_delay: N/A\n",
            "  Stream #0:1: Audio: aac (LC) (mp4a / 0x6134706D), 24000 Hz, mono, fltp, 69 kb/s\n",
            "    Metadata:\n",
            "      encoder         : Lavc58.134.100 aac\n",
            "frame= 1126 fps= 51 q=-1.0 Lsize=    2714kB time=00:00:37.63 bitrate= 590.8kbits/s speed= 1.7x    \n",
            "video:2357kB audio:328kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: 1.075360%\n",
            "\u001b[1;36m[libx264 @ 0x5b3adecf8100] \u001b[0mframe I:5     Avg QP:15.93  size: 20717\n",
            "\u001b[1;36m[libx264 @ 0x5b3adecf8100] \u001b[0mframe P:591   Avg QP:21.42  size:  3129\n",
            "\u001b[1;36m[libx264 @ 0x5b3adecf8100] \u001b[0mframe B:530   Avg QP:24.80  size:   869\n",
            "\u001b[1;36m[libx264 @ 0x5b3adecf8100] \u001b[0mconsecutive B-frames: 28.6% 24.0%  5.9% 41.6%\n",
            "\u001b[1;36m[libx264 @ 0x5b3adecf8100] \u001b[0mmb I  I16..4: 33.0% 55.5% 11.5%\n",
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            "\u001b[1;36m[libx264 @ 0x5b3adecf8100] \u001b[0m8x8 transform intra:77.1% inter:77.0%\n",
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          ]
        }
      ],
      "source": [
        "#@title Create Wav2Lip video (using wav2lip_gan.pth) GAN\n",
        "!cd Wav2Lip && python inference.py --checkpoint_path checkpoints/wav2lip_gan.pth --face '/content/gdrive/MyDrive/deepfake/input_video.mp4' --audio '/content/gdrive/MyDrive/deepfake/input_audio.wav' --resize_factor 2\n",
        "\n",
        "#Use --resize_factor 2 otherwise OOM error. Use resize_factor to reduce the video resolution, as there is a chance you might get better results for lower resolution videos.\n",
        "# This might be related with the model which might have been trained on low resolution faces."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "#@title Play result video -  50% scaling\n",
        "from IPython.display import HTML\n",
        "from base64 import b64encode\n",
        "mp4 = open('/content/Wav2Lip/results/result_voice.mp4','rb').read()\n",
        "\n",
        "data_url = \"data:video/mp4;base64,\" + b64encode(mp4).decode()\n",
        "HTML(f\"\"\"\n",
        "<video width=\"50%\" height=\"50%\" controls>\n",
        "      <source src=\"{data_url}\" type=\"video/mp4\">\n",
        "</video>\"\"\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "1kt-krsEbz5j"
      },
      "outputs": [],
      "source": [
        "#@title Download Result.mp4 to your computer\n",
        "from google.colab import files\n",
        "files.download('/content/Wav2Lip/results/result_voice.mp4') #Only after the last cell is executed this will start\n",
        "files.download('/content/gdrive/MyDrive/deepfake/input_audio.wav')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "fT8njpBCJ7gD"
      },
      "outputs": [],
      "source": [
        "# #@title Delete old uploaded samples & result files, so you can start over again.\n",
        "# # %rm /content/sample_data/*\n",
        "# %rm /content/Wav2Lip/results/*\n",
        "# from IPython.display import clear_output\n",
        "# clear_output()\n",
        "# print(\"\\nDone! now press X\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "d7zgfrQqbKom"
      },
      "source": [
        "# **Variations to try**\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "jmcEzPH3TDBg"
      },
      "outputs": [],
      "source": [
        "# #@title Create Wav2Lip video using wav2lip.pth\n",
        "# !cd Wav2Lip && python inference.py --checkpoint_path checkpoints/wav2lip.pth --face \"/content/sample_data/input_video.mp4\" --audio \"/content/sample_data/input_audio.wav\"  --resize_factor 2"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "45XW4SZAzIz5"
      },
      "outputs": [],
      "source": [
        "#@title Use more padding to include the chin region (you can manually edit pads dimensions viewing and changing the code)\n",
        "# !cd Wav2Lip && python inference.py --checkpoint_path checkpoints/wav2lip_gan.pth --face \"/content/sample_data/input_video.mp4\" --audio \"/content/sample_data/input_audio.wav\" --pads 0 20 0 0 --resize_factor 2"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "X1Z0zRdZR5BZ"
      },
      "outputs": [],
      "source": [
        "# #@title Play result video -  50% scaling\n",
        "# from IPython.display import HTML\n",
        "# from base64 import b64encode\n",
        "# mp4 = open('/content/Wav2Lip/results/result_voice.mp4','rb').read()\n",
        "# data_url = \"data:video/mp4;base64,\" + b64encode(mp4).decode()\n",
        "# HTML(f\"\"\"\n",
        "# <video width=\"50%\" height=\"50%\" controls>\n",
        "#       <source src=\"{data_url}\" type=\"video/mp4\">\n",
        "# </video>\"\"\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "gfXFOpAmR_dh"
      },
      "outputs": [],
      "source": [
        "#@title Download Result.mp4 to your computer\n",
        "# from google.colab import files\n",
        "# files.download('/content/Wav2Lip/results/result_voice.mp4')"
      ]
    }
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