Video_Translation_&_Lipsync.ipynb

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                  "Saving Musk tells boycotting advertisers to ‘go f--- yourself’.mp4 to Musk tells boycotting advertisers to ‘go f--- yourself’.mp4\n",
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            "  Stored in directory: /root/.cache/pip/wheels/9b/0a/90/788d92c07744b329b9283e37b29b064f5db6b1bb0442a1a19b\n",
            "  Building wheel for gruut_lang_fr (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for gruut_lang_fr: filename=gruut_lang_fr-2.0.2-py3-none-any.whl size=10968766 sha256=2c60a0308168e2465af6e88528e7a443441ca33ae4e5ab1a28d2fb7497fa6207\n",
            "  Stored in directory: /root/.cache/pip/wheels/db/21/be/d0436e3f1cf9bf38b9bb9b4a476399c77a1ab19f7172b45e19\n",
            "  Building wheel for gruut (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for gruut: filename=gruut-2.2.3-py3-none-any.whl size=75792 sha256=62708a2da48c94ce80871be3d905740bc65611ca58f69cc8ae6d21fe74b58d85\n",
            "  Stored in directory: /root/.cache/pip/wheels/fc/57/a8/f9de532daf5214f53644f20f3a9e6f69269453c87df9c0a817\n",
            "Successfully built encodec umap-learn bnnumerizer bnunicodenormalizer docopt gruut-ipa gruut_lang_de gruut_lang_en gruut_lang_es gruut_lang_fr gruut\n",
            "Installing collected packages: sudachipy, python-crfsuite, jamo, hangul-romanize, gruut_lang_fr, gruut_lang_es, gruut_lang_en, gruut_lang_de, docopt, bnunicodenormalizer, bnnumerizer, bangla, unidecode, sudachidict-core, pysbd, pypinyin, numpy, num2words, networkx, jsonlines, gruut-ipa, einops, coqpit, anyascii, g2pkk, dateparser, scikit-learn, gruut, pynndescent, librosa, encodec, umap-learn, trainer, TTS\n",
            "  Attempting uninstall: numpy\n",
            "    Found existing installation: numpy 1.23.5\n",
            "    Uninstalling numpy-1.23.5:\n",
            "      Successfully uninstalled numpy-1.23.5\n",
            "  Attempting uninstall: networkx\n",
            "    Found existing installation: networkx 3.2.1\n",
            "    Uninstalling networkx-3.2.1:\n",
            "      Successfully uninstalled networkx-3.2.1\n",
            "  Attempting uninstall: scikit-learn\n",
            "    Found existing installation: scikit-learn 1.2.2\n",
            "    Uninstalling scikit-learn-1.2.2:\n",
            "      Successfully uninstalled scikit-learn-1.2.2\n",
            "  Attempting uninstall: librosa\n",
            "    Found existing installation: librosa 0.10.1\n",
            "    Uninstalling librosa-0.10.1:\n",
            "      Successfully uninstalled librosa-0.10.1\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",
            "lida 0.0.10 requires fastapi, which is not installed.\n",
            "lida 0.0.10 requires kaleido, which is not installed.\n",
            "lida 0.0.10 requires python-multipart, which is not installed.\n",
            "lida 0.0.10 requires uvicorn, which is not installed.\n",
            "plotnine 0.12.4 requires numpy>=1.23.0, but you have numpy 1.22.0 which is incompatible.\n",
            "pywavelets 1.5.0 requires numpy<2.0,>=1.22.4, 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[0mSuccessfully installed TTS-0.22.0 anyascii-0.3.2 bangla-0.0.2 bnnumerizer-0.0.2 bnunicodenormalizer-0.1.6 coqpit-0.0.17 dateparser-1.1.8 docopt-0.6.2 einops-0.7.0 encodec-0.1.1 g2pkk-0.1.2 gruut-2.2.3 gruut-ipa-0.13.0 gruut_lang_de-2.0.0 gruut_lang_en-2.0.0 gruut_lang_es-2.0.0 gruut_lang_fr-2.0.2 hangul-romanize-0.1.0 jamo-0.4.1 jsonlines-1.2.0 librosa-0.10.0 networkx-2.8.8 num2words-0.5.13 numpy-1.22.0 pynndescent-0.5.11 pypinyin-0.50.0 pysbd-0.3.4 python-crfsuite-0.9.10 scikit-learn-1.3.2 sudachidict-core-20230927 sudachipy-0.6.8 trainer-0.0.36 umap-learn-0.5.5 unidecode-1.3.7\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.colab-display-data+json": {
              "pip_warning": {
                "packages": [
                  "numpy"
                ]
              }
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting numpy==1.24.0\n",
            "  Using cached numpy-1.24.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (17.3 MB)\n",
            "Installing collected packages: numpy\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",
            "\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",
            "lida 0.0.10 requires fastapi, which is not installed.\n",
            "lida 0.0.10 requires kaleido, which is not installed.\n",
            "lida 0.0.10 requires python-multipart, which is not installed.\n",
            "lida 0.0.10 requires uvicorn, which is not installed.\n",
            "tts 0.22.0 requires numpy==1.22.0; python_version <= \"3.10\", but you have numpy 1.24.0 which is incompatible.\n",
            "seaborn 0.12.2 requires numpy!=1.24.0,>=1.17, but you have numpy 1.24.0 which is incompatible.\u001b[0m\u001b[31m\n",
            "\u001b[0mSuccessfully installed numpy-1.24.0\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.colab-display-data+json": {
              "pip_warning": {
                "packages": [
                  "numpy"
                ]
              }
            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#Upload Video - Only supports 60 seconds max\n",
        "\n"
      ],
      "metadata": {
        "id": "natonJEOr369"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "id": "W2-ItJEbm73O",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 138,
          "referenced_widgets": [
            "3468a1aeea494572a0f1e12d73091dbc",
            "b7dd8443fb7b49ecad505cc59ea81cd7",
            "9bc52945fbbc4a5abb8a7ffc2833f3e5",
            "3268d0213a3f47ad90fe7188dcf122d0",
            "77005cb45c154a1fa1cb7c3685bef50f",
            "4d1d24afab4b49cd93a6fcfbc5e38887",
            "c6ce3c2d1bf34fce90117bc738b84320",
            "37a21aa630f14cb0be6917bd853a4828"
          ]
        },
        "outputId": "3a0e363c-7a93-45da-c614-bfad2034c732"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Checkbox(value=False, description='Resize to 720p (better results)')"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "3468a1aeea494572a0f1e12d73091dbc"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Button(description='Upload Video', style=ButtonStyle())"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "3268d0213a3f47ad90fe7188dcf122d0"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Output()"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "c6ce3c2d1bf34fce90117bc738b84320"
            }
          },
          "metadata": {}
        }
      ],
      "source": [
        "from google.colab import files\n",
        "import os\n",
        "import subprocess\n",
        "\n",
        "uploaded = None\n",
        "resize_to_720p = False\n",
        "\n",
        "def upload_video():\n",
        "  global uploaded\n",
        "  global video_path\n",
        "  uploaded = files.upload()\n",
        "  for filename in uploaded.keys():\n",
        "    print(f'Uploaded {filename}')\n",
        "    if resize_to_720p:\n",
        "        filename = resize_video(filename)\n",
        "    video_path = filename\n",
        "    return filename\n",
        "\n",
        "\n",
        "def resize_video(filename):\n",
        "    output_filename = f\"resized_{filename}\"\n",
        "    cmd = f\"ffmpeg -i {filename} -vf scale=-1:720 {output_filename}\"\n",
        "    subprocess.run(cmd, shell=True)\n",
        "    print(f'Resized video saved as {output_filename}')\n",
        "    return output_filename\n",
        "\n",
        "import ipywidgets as widgets\n",
        "from IPython.display import display\n",
        "\n",
        "button = widgets.Button(description=\"Upload Video\")\n",
        "checkbox = widgets.Checkbox(value=False, description='Resize to 720p (better results)')\n",
        "output = widgets.Output()\n",
        "\n",
        "def on_button_clicked(b):\n",
        "  with output:\n",
        "    global video_path\n",
        "    global resize_to_720p\n",
        "    resize_to_720p = checkbox.value\n",
        "    video_path = upload_video()\n",
        "\n",
        "button.on_click(on_button_clicked)\n",
        "display(checkbox, button, output)"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#Extract Audio Text From Video - Whisper\n"
      ],
      "metadata": {
        "id": "sFcXWp3nsnAB"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "https://github.com/openai/whisper"
      ],
      "metadata": {
        "id": "B6EJG8sGuggc"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install git+https://github.com/openai/whisper.git"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pI0C4MjMs4AR",
        "outputId": "177d539d-410c-4fce-867a-009bbd221efb"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting git+https://github.com/openai/whisper.git\n",
            "  Cloning https://github.com/openai/whisper.git to /tmp/pip-req-build-6c4e00ml\n",
            "  Running command git clone --filter=blob:none --quiet https://github.com/openai/whisper.git /tmp/pip-req-build-6c4e00ml\n",
            "  Resolved https://github.com/openai/whisper.git to commit ba3f3cd54b0e5b8ce1ab3de13e32122d0d5f98ab\n",
            "  Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
            "  Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n",
            "  Preparing metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
            "Requirement already satisfied: numba in /usr/local/lib/python3.10/dist-packages (from openai-whisper==20231117) (0.58.1)\n",
            "Requirement already satisfied: numpy in /usr/local/lib/python3.10/dist-packages (from openai-whisper==20231117) (1.22.0)\n",
            "Requirement already satisfied: torch in /usr/local/lib/python3.10/dist-packages (from openai-whisper==20231117) (2.1.0+cu121)\n",
            "Requirement already satisfied: tqdm in /usr/local/lib/python3.10/dist-packages (from openai-whisper==20231117) (4.66.1)\n",
            "Requirement already satisfied: more-itertools in /usr/local/lib/python3.10/dist-packages (from openai-whisper==20231117) (10.1.0)\n",
            "Collecting tiktoken (from openai-whisper==20231117)\n",
            "  Downloading tiktoken-0.5.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.0 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m2.0/2.0 MB\u001b[0m \u001b[31m25.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: triton<3,>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from openai-whisper==20231117) (2.1.0)\n",
            "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from triton<3,>=2.0.0->openai-whisper==20231117) (3.13.1)\n",
            "Requirement already satisfied: llvmlite<0.42,>=0.41.0dev0 in /usr/local/lib/python3.10/dist-packages (from numba->openai-whisper==20231117) (0.41.1)\n",
            "Requirement already satisfied: regex>=2022.1.18 in /usr/local/lib/python3.10/dist-packages (from tiktoken->openai-whisper==20231117) (2023.6.3)\n",
            "Requirement already satisfied: requests>=2.26.0 in /usr/local/lib/python3.10/dist-packages (from tiktoken->openai-whisper==20231117) (2.31.0)\n",
            "Requirement already satisfied: typing-extensions in /usr/local/lib/python3.10/dist-packages (from torch->openai-whisper==20231117) (4.5.0)\n",
            "Requirement already satisfied: sympy in /usr/local/lib/python3.10/dist-packages (from torch->openai-whisper==20231117) (1.12)\n",
            "Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (from torch->openai-whisper==20231117) (2.8.8)\n",
            "Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from torch->openai-whisper==20231117) (3.1.2)\n",
            "Requirement already satisfied: fsspec in /usr/local/lib/python3.10/dist-packages (from torch->openai-whisper==20231117) (2023.6.0)\n",
            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests>=2.26.0->tiktoken->openai-whisper==20231117) (3.3.2)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests>=2.26.0->tiktoken->openai-whisper==20231117) (3.6)\n",
            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests>=2.26.0->tiktoken->openai-whisper==20231117) (2.0.7)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests>=2.26.0->tiktoken->openai-whisper==20231117) (2023.11.17)\n",
            "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch->openai-whisper==20231117) (2.1.3)\n",
            "Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.10/dist-packages (from sympy->torch->openai-whisper==20231117) (1.3.0)\n",
            "Building wheels for collected packages: openai-whisper\n",
            "  Building wheel for openai-whisper (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for openai-whisper: filename=openai_whisper-20231117-py3-none-any.whl size=802825 sha256=0d634010736ae5cdae6d4a50fa67b0aad54f1a9d731133bcc16e491d7a356ffd\n",
            "  Stored in directory: /tmp/pip-ephem-wheel-cache-to581km2/wheels/8b/6c/d0/622666868c179f156cf595c8b6f06f88bc5d80c4b31dccaa03\n",
            "Successfully built openai-whisper\n",
            "Installing collected packages: tiktoken, openai-whisper\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",
            "llmx 0.0.15a0 requires cohere, which is not installed.\n",
            "llmx 0.0.15a0 requires openai, which is not installed.\u001b[0m\u001b[31m\n",
            "\u001b[0mSuccessfully installed openai-whisper-20231117 tiktoken-0.5.2\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import subprocess\n",
        "\n",
        "# Ensure video_path variable exists\n",
        "if 'video_path' in globals() and video_path is not None:\n",
        "    ffmpeg_command = f\"ffmpeg -i '{video_path}' -acodec pcm_s24le -ar 48000 -q:a 0 -map a -y 'output_audio.wav'\"\n",
        "    subprocess.run(ffmpeg_command, shell=True)\n",
        "else:\n",
        "    print(\"No video uploaded. Please upload a video first.\")\n",
        "\n",
        "import whisper\n",
        "\n",
        "model = whisper.load_model(\"base\")\n",
        "result = model.transcribe(\"output_audio.wav\")\n",
        "\n",
        "whisper_text = result[\"text\"]\n",
        "whisper_language = result['language']\n",
        "\n",
        "print(\"Audio text:\", whisper_text)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "dr3CCGHDsmY6",
        "outputId": "00647db6-2a6e-42ab-ab04-e51b1413df59"
      },
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "No video uploaded. Please upload a video first.\n",
            "Audio text:  I hope they stop. You hope... Don't advertise. You don't want them to advertise? No. What do you mean? If somebody's gonna try to blackmail me with advertising, blackmail me with money, go f*** yourself. But... Go... F*** yourself. Is that clear? I hope it is. Hey, Bob. You're in the audience. Well, let me ask you then... That's all I feel. Don't advertise.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#Translation"
      ],
      "metadata": {
        "id": "AE25W4XDtcfp"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install googletrans==4.0.0-rc1"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "WZLu_BnZuGSg",
        "outputId": "fb9a7eba-1658-4d8a-ae90-ef4fff7ede4b"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting googletrans==4.0.0-rc1\n",
            "  Downloading googletrans-4.0.0rc1.tar.gz (20 kB)\n",
            "  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "Collecting httpx==0.13.3 (from googletrans==4.0.0-rc1)\n",
            "  Downloading httpx-0.13.3-py3-none-any.whl (55 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m55.1/55.1 kB\u001b[0m \u001b[31m1.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: certifi in /usr/local/lib/python3.10/dist-packages (from httpx==0.13.3->googletrans==4.0.0-rc1) (2023.11.17)\n",
            "Collecting hstspreload (from httpx==0.13.3->googletrans==4.0.0-rc1)\n",
            "  Downloading hstspreload-2023.1.1-py3-none-any.whl (1.5 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.5/1.5 MB\u001b[0m \u001b[31m30.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: sniffio in /usr/local/lib/python3.10/dist-packages (from httpx==0.13.3->googletrans==4.0.0-rc1) (1.3.0)\n",
            "Collecting chardet==3.* (from httpx==0.13.3->googletrans==4.0.0-rc1)\n",
            "  Downloading chardet-3.0.4-py2.py3-none-any.whl (133 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m133.4/133.4 kB\u001b[0m \u001b[31m19.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting idna==2.* (from httpx==0.13.3->googletrans==4.0.0-rc1)\n",
            "  Downloading idna-2.10-py2.py3-none-any.whl (58 kB)\n",
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            "\u001b[?25hCollecting rfc3986<2,>=1.3 (from httpx==0.13.3->googletrans==4.0.0-rc1)\n",
            "  Downloading rfc3986-1.5.0-py2.py3-none-any.whl (31 kB)\n",
            "Collecting httpcore==0.9.* (from httpx==0.13.3->googletrans==4.0.0-rc1)\n",
            "  Downloading httpcore-0.9.1-py3-none-any.whl (42 kB)\n",
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            "\u001b[?25hCollecting h11<0.10,>=0.8 (from httpcore==0.9.*->httpx==0.13.3->googletrans==4.0.0-rc1)\n",
            "  Downloading h11-0.9.0-py2.py3-none-any.whl (53 kB)\n",
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            "\u001b[?25hCollecting h2==3.* (from httpcore==0.9.*->httpx==0.13.3->googletrans==4.0.0-rc1)\n",
            "  Downloading h2-3.2.0-py2.py3-none-any.whl (65 kB)\n",
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            "\u001b[?25hCollecting hyperframe<6,>=5.2.0 (from h2==3.*->httpcore==0.9.*->httpx==0.13.3->googletrans==4.0.0-rc1)\n",
            "  Downloading hyperframe-5.2.0-py2.py3-none-any.whl (12 kB)\n",
            "Collecting hpack<4,>=3.0 (from h2==3.*->httpcore==0.9.*->httpx==0.13.3->googletrans==4.0.0-rc1)\n",
            "  Downloading hpack-3.0.0-py2.py3-none-any.whl (38 kB)\n",
            "Building wheels for collected packages: googletrans\n",
            "  Building wheel for googletrans (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for googletrans: filename=googletrans-4.0.0rc1-py3-none-any.whl size=17396 sha256=b04c55e66034408ca3f9b7ac887b058b0213972050c9bc36c543d453621e044f\n",
            "  Stored in directory: /root/.cache/pip/wheels/c0/59/9f/7372f0cf70160fe61b528532e1a7c8498c4becd6bcffb022de\n",
            "Successfully built googletrans\n",
            "Installing collected packages: rfc3986, hyperframe, hpack, h11, chardet, idna, hstspreload, h2, httpcore, httpx, googletrans\n",
            "  Attempting uninstall: chardet\n",
            "    Found existing installation: chardet 5.2.0\n",
            "    Uninstalling chardet-5.2.0:\n",
            "      Successfully uninstalled chardet-5.2.0\n",
            "  Attempting uninstall: idna\n",
            "    Found existing installation: idna 3.6\n",
            "    Uninstalling idna-3.6:\n",
            "      Successfully uninstalled idna-3.6\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",
            "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[0mSuccessfully installed chardet-3.0.4 googletrans-4.0.0rc1 h11-0.9.0 h2-3.2.0 hpack-3.0.0 hstspreload-2023.1.1 httpcore-0.9.1 httpx-0.13.3 hyperframe-5.2.0 idna-2.10 rfc3986-1.5.0\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "target_language = \"French\" #@param [\"English\", \"Spanish\", \"French\", \"German\", \"Italian\", \"Portuguese\", \"Polish\", \"Turkish\", \"Russian\", \"Dutch\", \"Czech\", \"Arabic\", \"Chinese (Simplified)\"]\n",
        "\n",
        "# Mapping between full names and ISO 639-1 codes\n",
        "language_mapping = {\n",
        "    'English': 'en',\n",
        "    'Spanish': 'es',\n",
        "    'French': 'fr',\n",
        "    'German': 'de',\n",
        "    'Italian': 'it',\n",
        "    'Portuguese': 'pt',\n",
        "    'Polish': 'pl',\n",
        "    'Turkish': 'tr',\n",
        "    'Russian': 'ru',\n",
        "    'Dutch': 'nl',\n",
        "    'Czech': 'cs',\n",
        "    'Arabic': 'ar',\n",
        "    'Chinese (Simplified)': 'zh-cn'\n",
        "}\n",
        "\n",
        "target_language_code = language_mapping[target_language]\n",
        "from googletrans import Translator\n",
        "translator = Translator()\n",
        "translated_text = translator.translate(whisper_text, src=whisper_language, dest=target_language_code).text\n",
        "print(\"Translated text:\", translated_text)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "uvdpJLA9tnrf",
        "outputId": "76cdfb4a-db77-40e0-c8ad-04b936ffe9cb"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Translated text: J'espère qu'ils s'arrêtent.Vous espérez ... ne faites pas de publicité.Vous ne voulez pas qu'ils font de la publicité?Non. Que voulez-vous dire?Si quelqu'un va essayer de me faire chanter avec de la publicité, me faire chanter avec de l'argent, allez-y.Mais ... Allez ... F *** vous-même.Est-ce clair?Je l'espère.Hé, Bob.Vous êtes dans le public.Eh bien, laissez-moi vous demander alors ... c'est tout ce que je ressens.Ne faites pas de publicité.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "\n",
        "\n",
        "#Voice Synthesis"
      ],
      "metadata": {
        "id": "2Z78OCLjuV2n"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "https://github.com/coqui-ai/TTS"
      ],
      "metadata": {
        "id": "7myhxlNxue2a"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from TTS.api import TTS\n",
        "import torch\n",
        "from IPython.display import Audio, display\n",
        "\n",
        "tts = TTS(\"tts_models/multilingual/multi-dataset/xtts_v2\", gpu=True).to(\"cuda\")\n",
        "\n",
        "#generate audio\n",
        "tts.tts_to_file(translated_text,\n",
        "    speaker_wav='output_audio.wav',\n",
        "    file_path=\"output_synth.wav\",\n",
        "    language=target_language_code\n",
        ")\n",
        "audio_widget = Audio(filename=\"output_synth.wav\", autoplay=False)\n",
        "display(audio_widget)"
      ],
      "metadata": {
        "id": "COmPIk3Ku0TH"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "#**Important**\n",
        "If you are on Google Colab free version (T4), Delete TTS and Whisper at this step"
      ],
      "metadata": {
        "id": "6iEqEoaBvBjy"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import torch\n",
        "\n",
        "try:\n",
        "    del tts\n",
        "except NameError:\n",
        "    print(\"Voice model already deleted\")\n",
        "\n",
        "try:\n",
        "    del model\n",
        "except NameError:\n",
        "    print(\"Whisper model already deleted\")\n",
        "\n",
        "torch.cuda.empty_cache()"
      ],
      "metadata": {
        "id": "5wRr7LZNvWqf"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "#Lip Sync - High Quality\n",
        "Takes arround 15 mins approx for installation on free colab version (T4)"
      ],
      "metadata": {
        "id": "0ByUfwRZvZ3V"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "https://github.com/OpenTalker/video-retalking"
      ],
      "metadata": {
        "id": "2Kxu-WiLwdU5"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Dependencies\n",
        "%cd /content/\n",
        "\n",
        "import locale\n",
        "locale.getpreferredencoding = lambda: \"UTF-8\"\n",
        "\n",
        "!git clone https://github.com/vinthony/video-retalking.git &> /dev/null\n",
        "\n",
        "!sudo apt-get install -y libblas-dev liblapack-dev libx11-dev libopenblas-dev\n",
        "\n",
        "!git clone https://github.com/davisking/dlib.git\n",
        "\n",
        "!pip install basicsr==1.4.2 face-alignment==1.3.4 kornia==0.5.1 ninja==1.10.2.3 einops==0.4.1 facexlib==0.2.5 librosa==0.9.2 build\n",
        "\n",
        "!cd dlib && python setup.py install\n",
        "\n",
        "%cd /content/video-retalking\n",
        "\n",
        "!mkdir ./checkpoints\n",
        "!wget https://github.com/vinthony/video-retalking/releases/download/v0.0.1/30_net_gen.pth -O ./checkpoints/30_net_gen.pth\n",
        "!wget https://github.com/vinthony/video-retalking/releases/download/v0.0.1/BFM.zip -O ./checkpoints/BFM.zip\n",
        "!wget https://github.com/vinthony/video-retalking/releases/download/v0.0.1/DNet.pt -O ./checkpoints/DNet.pt\n",
        "!wget https://github.com/vinthony/video-retalking/releases/download/v0.0.1/ENet.pth -O ./checkpoints/ENet.pth\n",
        "!wget https://github.com/vinthony/video-retalking/releases/download/v0.0.1/expression.mat -O ./checkpoints/expression.mat\n",
        "!wget https://github.com/vinthony/video-retalking/releases/download/v0.0.1/face3d_pretrain_epoch_20.pth -O ./checkpoints/face3d_pretrain_epoch_20.pth\n",
        "!wget https://github.com/vinthony/video-retalking/releases/download/v0.0.1/GFPGANv1.3.pth -O ./checkpoints/GFPGANv1.3.pth\n",
        "!wget https://github.com/vinthony/video-retalking/releases/download/v0.0.1/GPEN-BFR-512.pth -O ./checkpoints/GPEN-BFR-512.pth\n",
        "!wget https://github.com/vinthony/video-retalking/releases/download/v0.0.1/LNet.pth -O ./checkpoints/LNet.pth\n",
        "!wget https://github.com/vinthony/video-retalking/releases/download/v0.0.1/ParseNet-latest.pth -O ./checkpoints/ParseNet-latest.pth\n",
        "!wget https://github.com/vinthony/video-retalking/releases/download/v0.0.1/RetinaFace-R50.pth -O ./checkpoints/RetinaFace-R50.pth\n",
        "!wget https://github.com/vinthony/video-retalking/releases/download/v0.0.1/shape_predictor_68_face_landmarks.dat -O ./checkpoints/shape_predictor_68_face_landmarks.dat\n",
        "!unzip -d ./checkpoints/BFM ./checkpoints/BFM.zip"
      ],
      "metadata": {
        "id": "f_a6Q_AwvpFQ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#Generate video\n",
        "\n",
        "%cd /content/video-retalking\n",
        "\n",
        "video_path_fix = f\"'../{video_path}'\"\n",
        "\n",
        "!python inference.py \\\n",
        "  --face $video_path_fix \\\n",
        "  --audio \"/content/output_synth.wav\" \\\n",
        "  --outfile '/content/output_high_qual.mp4'"
      ],
      "metadata": {
        "id": "2ecglT2Lwi61"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "#Lip Sync - Normal Quality\n",
        "Takes arround 5 mins approx for installation on free colab version (T4)."
      ],
      "metadata": {
        "id": "ZXhEOsSZwm49"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "https://github.com/justinjohn0306/Wav2Lip"
      ],
      "metadata": {
        "id": "phtcGJK-xLuj"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Dependencies\n",
        "%cd /content/\n",
        "\n",
        "import locale\n",
        "locale.getpreferredencoding = lambda: \"UTF-8\"\n",
        "\n",
        "!git clone https://github.com/justinjohn0306/Wav2Lip\n",
        "!cd Wav2Lip && pip install -r requirements_colab.txt\n",
        "\n",
        "%cd /content/Wav2Lip\n",
        "\n",
        "!wget \"https://www.adrianbulat.com/downloads/python-fan/s3fd-619a316812.pth\" -O \"face_detection/detection/sfd/s3fd.pth\"\n",
        "!wget 'https://github.com/justinjohn0306/Wav2Lip/releases/download/models/wav2lip.pth' -O 'checkpoints/wav2lip.pth'\n",
        "!wget 'https://github.com/justinjohn0306/Wav2Lip/releases/download/models/wav2lip_gan.pth' -O 'checkpoints/wav2lip_gan.pth'\n",
        "!wget 'https://github.com/justinjohn0306/Wav2Lip/releases/download/models/resnet50.pth' -O 'checkpoints/resnet50.pth'\n",
        "!wget 'https://github.com/justinjohn0306/Wav2Lip/releases/download/models/mobilenet.pth' -O 'checkpoints/mobilenet.pth'\n",
        "\n",
        "!pip install batch-face"
      ],
      "metadata": {
        "id": "A_Tn2hKbxJJO",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "09d260bd-7d4b-49c6-b5c2-d176298fc228"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content\n",
            "Cloning into 'Wav2Lip'...\n",
            "remote: Enumerating objects: 502, done.\u001b[K\n",
            "remote: Counting objects: 100% (81/81), done.\u001b[K\n",
            "remote: Compressing objects: 100% (61/61), done.\u001b[K\n",
            "remote: Total 502 (delta 24), reused 69 (delta 18), pack-reused 421\u001b[K\n",
            "Receiving objects: 100% (502/502), 29.76 MiB | 10.76 MiB/s, done.\n",
            "Resolving deltas: 100% (257/257), done.\n",
            "Collecting numpy==1.23.4 (from -r requirements_colab.txt (line 1))\n",
            "  Downloading numpy-1.23.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (17.1 MB)\n",
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            "Requirement already satisfied: cffi>=1.0 in /usr/local/lib/python3.10/dist-packages (from soundfile>=0.12.1->librosa->-r requirements_colab.txt (line 2)) (1.16.0)\n",
            "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch->-r requirements_colab.txt (line 4)) (2.1.3)\n",
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            "Requirement already satisfied: pycparser in /usr/local/lib/python3.10/dist-packages (from cffi>=1.0->soundfile>=0.12.1->librosa->-r requirements_colab.txt (line 2)) (2.21)\n",
            "Installing collected packages: numpy\n",
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            "    Uninstalling numpy-1.24.0:\n",
            "      Successfully uninstalled numpy-1.24.0\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",
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            "tts 0.22.0 requires numpy==1.22.0; python_version <= \"3.10\", but you have numpy 1.23.4 which is incompatible.\n",
            "tensorflow 2.15.0 requires numpy<2.0.0,>=1.23.5, but you have numpy 1.23.4 which is incompatible.\u001b[0m\u001b[31m\n",
            "\u001b[0mSuccessfully installed numpy-1.23.4\n",
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            "\n",
            "Collecting batch-face\n",
            "  Downloading batch_face-1.4.0-py3-none-any.whl (30.6 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m30.6/30.6 MB\u001b[0m \u001b[31m19.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: numpy in /usr/local/lib/python3.10/dist-packages (from batch-face) (1.23.4)\n",
            "Requirement already satisfied: torch in /usr/local/lib/python3.10/dist-packages (from batch-face) (2.1.0+cu121)\n",
            "Requirement already satisfied: torchvision in /usr/local/lib/python3.10/dist-packages (from batch-face) (0.16.0+cu121)\n",
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            "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from torch->batch-face) (3.13.1)\n",
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            "Requirement already satisfied: fsspec in /usr/local/lib/python3.10/dist-packages (from torch->batch-face) (2023.6.0)\n",
            "Requirement already satisfied: triton==2.1.0 in /usr/local/lib/python3.10/dist-packages (from torch->batch-face) (2.1.0)\n",
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            "Requirement already satisfied: pillow!=8.3.*,>=5.3.0 in /usr/local/lib/python3.10/dist-packages (from torchvision->batch-face) (9.4.0)\n",
            "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch->batch-face) (2.1.3)\n",
            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->torchvision->batch-face) (3.3.2)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->torchvision->batch-face) (2.10)\n",
            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->torchvision->batch-face) (2.0.7)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->torchvision->batch-face) (2023.11.17)\n",
            "Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.10/dist-packages (from sympy->torch->batch-face) (1.3.0)\n",
            "Installing collected packages: batch-face\n",
            "Successfully installed batch-face-1.4.0\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Generate video\n",
        "\n",
        "%cd /content/Wav2Lip\n",
        "\n",
        "#This is the detection box padding, if you see it doesnt sit quite right, just adjust the values a bit. Usually the bottom one is the biggest issue\n",
        "pad_top =  0\n",
        "pad_bottom =  15\n",
        "pad_left =  0\n",
        "pad_right =  0\n",
        "rescaleFactor =  1\n",
        "\n",
        "video_path_fix = f\"'../{video_path}'\"\n",
        "\n",
        "!python inference.py --checkpoint_path 'checkpoints/wav2lip_gan.pth' --face $video_path_fix --audio \"/content/output_synth.wav\" --pads $pad_top $pad_bottom $pad_left $pad_right --resize_factor $rescaleFactor --nosmooth --outfile '/content/output_video.mp4'\n"
      ],
      "metadata": {
        "id": "N7SaNwEuxOnM",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "d71a0827-2094-4475-db9f-af7932902533"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/Wav2Lip\n",
            "Using cuda for inference.\n",
            "Load checkpoint from: checkpoints/wav2lip_gan.pth\n",
            "Models loaded\n",
            "Reading video frames...\n",
            "Number of frames available for inference: 1022\n",
            "(80, 5527)\n",
            "Length of mel chunks: 1724\n",
            "  0% 0/14 [00:00<?, ?it/s]face detect time: 125.64418029785156\n",
            "100% 14/14 [02:31<00:00, 10.80s/it]\n",
            "wav2lip prediction time: 151.15052485466003\n",
            "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",
            "Input #0, avi, from 'temp/result.avi':\n",
            "  Metadata:\n",
            "    software        : Lavf59.27.100\n",
            "  Duration: 00:01:08.96, start: 0.000000, bitrate: 1618 kb/s\n",
            "  Stream #0:0: Video: mpeg4 (Simple Profile) (DIVX / 0x58564944), yuv420p, 852x480 [SAR 1:1 DAR 71:40], 1614 kb/s, 25 fps, 25 tbr, 25 tbn, 25 tbc\n",
            "\u001b[0;33mGuessed Channel Layout for Input Stream #1.0 : mono\n",
            "\u001b[0mInput #1, wav, from '/content/output_synth.wav':\n",
            "  Duration: 00:01:09.08, bitrate: 384 kb/s\n",
            "  Stream #1:0: Audio: pcm_s16le ([1][0][0][0] / 0x0001), 24000 Hz, mono, s16, 384 kb/s\n",
            "Stream mapping:\n",
            "  Stream #0:0 -> #0:0 (mpeg4 (native) -> h264 (libx264))\n",
            "  Stream #1:0 -> #0:1 (pcm_s16le (native) -> aac (native))\n",
            "Press [q] to stop, [?] for help\n",
            "\u001b[1;36m[libx264 @ 0x5a180a42e640] \u001b[0musing SAR=1/1\n",
            "\u001b[1;36m[libx264 @ 0x5a180a42e640] \u001b[0musing cpu capabilities: MMX2 SSE2Fast SSSE3 SSE4.2 AVX FMA3 BMI2 AVX2 AVX512\n",
            "\u001b[1;36m[libx264 @ 0x5a180a42e640] \u001b[0mprofile High, level 3.0, 4:2:0, 8-bit\n",
            "\u001b[1;36m[libx264 @ 0x5a180a42e640] \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 '/content/output_video.mp4':\n",
            "  Metadata:\n",
            "    software        : Lavf59.27.100\n",
            "    encoder         : Lavf58.76.100\n",
            "  Stream #0:0: Video: h264 (avc1 / 0x31637661), yuv420p(progressive), 852x480 [SAR 1:1 DAR 71:40], q=2-31, 25 fps, 12800 tbn\n",
            "    Metadata:\n",
            "      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= 1724 fps= 57 q=-1.0 Lsize=    4829kB time=00:01:09.03 bitrate= 573.0kbits/s speed=2.27x    \n",
            "video:4224kB audio:564kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: 0.843633%\n",
            "\u001b[1;36m[libx264 @ 0x5a180a42e640] \u001b[0mframe I:10    Avg QP:16.90  size: 26924\n",
            "\u001b[1;36m[libx264 @ 0x5a180a42e640] \u001b[0mframe P:794   Avg QP:20.76  size:  4232\n",
            "\u001b[1;36m[libx264 @ 0x5a180a42e640] \u001b[0mframe B:920   Avg QP:23.56  size:   756\n",
            "\u001b[1;36m[libx264 @ 0x5a180a42e640] \u001b[0mconsecutive B-frames: 23.0% 14.3% 10.1% 52.7%\n",
            "\u001b[1;36m[libx264 @ 0x5a180a42e640] \u001b[0mmb I  I16..4: 28.1% 57.3% 14.6%\n",
            "\u001b[1;36m[libx264 @ 0x5a180a42e640] \u001b[0mmb P  I16..4:  2.3%  6.4%  0.2%  P16..4: 22.0%  6.9%  4.3%  0.0%  0.0%    skip:57.9%\n",
            "\u001b[1;36m[libx264 @ 0x5a180a42e640] \u001b[0mmb B  I16..4:  0.3%  0.8%  0.0%  B16..8: 24.4%  1.5%  0.2%  direct: 0.7%  skip:72.2%  L0:47.8% L1:47.0% BI: 5.2%\n",
            "\u001b[1;36m[libx264 @ 0x5a180a42e640] \u001b[0m8x8 transform intra:70.2% inter:69.3%\n",
            "\u001b[1;36m[libx264 @ 0x5a180a42e640] \u001b[0mcoded y,uvDC,uvAC intra: 25.0% 39.5% 10.7% inter: 5.4% 5.6% 0.6%\n",
            "\u001b[1;36m[libx264 @ 0x5a180a42e640] \u001b[0mi16 v,h,dc,p: 26% 53% 16%  5%\n",
            "\u001b[1;36m[libx264 @ 0x5a180a42e640] \u001b[0mi8 v,h,dc,ddl,ddr,vr,hd,vl,hu: 20% 29% 46%  1%  1%  1%  1%  1%  1%\n",
            "\u001b[1;36m[libx264 @ 0x5a180a42e640] \u001b[0mi4 v,h,dc,ddl,ddr,vr,hd,vl,hu: 32% 26% 15%  4%  4%  6%  4%  4%  4%\n",
            "\u001b[1;36m[libx264 @ 0x5a180a42e640] \u001b[0mi8c dc,h,v,p: 45% 37% 16%  3%\n",
            "\u001b[1;36m[libx264 @ 0x5a180a42e640] \u001b[0mWeighted P-Frames: Y:1.9% UV:0.1%\n",
            "\u001b[1;36m[libx264 @ 0x5a180a42e640] \u001b[0mref P L0: 70.7% 10.1% 14.3%  4.9%  0.1%\n",
            "\u001b[1;36m[libx264 @ 0x5a180a42e640] \u001b[0mref B L0: 83.1% 14.2%  2.7%\n",
            "\u001b[1;36m[libx264 @ 0x5a180a42e640] \u001b[0mref B L1: 95.5%  4.5%\n",
            "\u001b[1;36m[libx264 @ 0x5a180a42e640] \u001b[0mkb/s:501.73\n",
            "\u001b[1;36m[aac @ 0x5a180a430080] \u001b[0mQavg: 8364.447\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#Download videos"
      ],
      "metadata": {
        "id": "NPzHEZxAxSxc"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import files\n",
        "from IPython.core.display import display, HTML\n",
        "import ipywidgets as widgets\n",
        "import base64\n",
        "import os\n",
        "\n",
        "# List of video paths to check\n",
        "video_paths = [\"/content/output_video.mp4\", \"/content/output_high_qual.mp4\"]\n",
        "\n",
        "def download_video(b):\n",
        "    files.download(b.video_path)\n",
        "\n",
        "download_buttons = []\n",
        "\n",
        "# Layout definition for button\n",
        "button_layout = widgets.Layout(width='250px')\n",
        "\n",
        "# Loop through each video path to check for existence and display\n",
        "for video_path in video_paths:\n",
        "    if os.path.exists(video_path):\n",
        "        # Encode video base64\n",
        "        with open(video_path, \"rb\") as video_file:\n",
        "            video_base64 = base64.b64encode(video_file.read()).decode()\n",
        "\n",
        "        # HTML widget for video\n",
        "        video_html = HTML(data=f\"\"\"\n",
        "        <video width=400 controls>\n",
        "            <source src=\"data:video/mp4;base64,{video_base64}\" type=\"video/mp4\" />\n",
        "        </video>\n",
        "        \"\"\")\n",
        "\n",
        "        # button widget for download and link to the video path\n",
        "        download_button = widgets.Button(description=f\"Download {os.path.basename(video_path)}\",\n",
        "                                         layout=button_layout)\n",
        "        download_button.video_path = video_path\n",
        "        download_button.on_click(download_video)\n",
        "        download_buttons.append(download_button)\n",
        "\n",
        "        # Display widgets\n",
        "        display(video_html)\n",
        "        display(download_button)\n"
      ],
      "metadata": {
        "id": "KB0TmaBHxYcQ"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}