main.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "main.ipynb",
      "provenance": [],
      "machine_shape": "hm"
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "oCXUUPOaWqLO",
        "outputId": "0bd25f7a-aa3d-425a-efa8-a45c5c060a4e",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "!git clone https://github.com/AliaksandrSiarohin/first-order-model\n",
        "!git clone https://github.com/snoop2head/Fun_Cool_Sexy_Damedane"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Cloning into 'first-order-model'...\n",
            "remote: Enumerating objects: 393, done.\u001b[K\n",
            "remote: Total 393 (delta 0), reused 0 (delta 0), pack-reused 393 (from 1)\u001b[K\n",
            "Receiving objects: 100% (393/393), 72.19 MiB | 11.60 MiB/s, done.\n",
            "Resolving deltas: 100% (203/203), done.\n",
            "Updating files: 100% (48/48), done.\n",
            "Cloning into 'Fun_Cool_Sexy_Damedane'...\n",
            "remote: Enumerating objects: 49, done.\u001b[K\n",
            "remote: Counting objects: 100% (6/6), done.\u001b[K\n",
            "remote: Compressing objects: 100% (5/5), done.\u001b[K\n",
            "remote: Total 49 (delta 5), reused 1 (delta 1), pack-reused 43 (from 1)\u001b[K\n",
            "Receiving objects: 100% (49/49), 9.36 MiB | 15.36 MiB/s, done.\n",
            "Resolving deltas: 100% (21/21), done.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sRBDrQ_EtOWj",
        "outputId": "11460fa3-d314-4a51-d293-a00d482f4b0b",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "!pip install PyDrive"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: PyDrive in /usr/local/lib/python3.10/dist-packages (1.3.1)\n",
            "Requirement already satisfied: google-api-python-client>=1.2 in /usr/local/lib/python3.10/dist-packages (from PyDrive) (2.137.0)\n",
            "Requirement already satisfied: oauth2client>=4.0.0 in /usr/local/lib/python3.10/dist-packages (from PyDrive) (4.1.3)\n",
            "Requirement already satisfied: PyYAML>=3.0 in /usr/local/lib/python3.10/dist-packages (from PyDrive) (6.0.2)\n",
            "Requirement already satisfied: httplib2<1.dev0,>=0.19.0 in /usr/local/lib/python3.10/dist-packages (from google-api-python-client>=1.2->PyDrive) (0.22.0)\n",
            "Requirement already satisfied: google-auth!=2.24.0,!=2.25.0,<3.0.0.dev0,>=1.32.0 in /usr/local/lib/python3.10/dist-packages (from google-api-python-client>=1.2->PyDrive) (2.27.0)\n",
            "Requirement already satisfied: google-auth-httplib2<1.0.0,>=0.2.0 in /usr/local/lib/python3.10/dist-packages (from google-api-python-client>=1.2->PyDrive) (0.2.0)\n",
            "Requirement already satisfied: google-api-core!=2.0.*,!=2.1.*,!=2.2.*,!=2.3.0,<3.0.0.dev0,>=1.31.5 in /usr/local/lib/python3.10/dist-packages (from google-api-python-client>=1.2->PyDrive) (2.19.2)\n",
            "Requirement already satisfied: uritemplate<5,>=3.0.1 in /usr/local/lib/python3.10/dist-packages (from google-api-python-client>=1.2->PyDrive) (4.1.1)\n",
            "Requirement already satisfied: pyasn1>=0.1.7 in /usr/local/lib/python3.10/dist-packages (from oauth2client>=4.0.0->PyDrive) (0.6.1)\n",
            "Requirement already satisfied: pyasn1-modules>=0.0.5 in /usr/local/lib/python3.10/dist-packages (from oauth2client>=4.0.0->PyDrive) (0.4.1)\n",
            "Requirement already satisfied: rsa>=3.1.4 in /usr/local/lib/python3.10/dist-packages (from oauth2client>=4.0.0->PyDrive) (4.9)\n",
            "Requirement already satisfied: six>=1.6.1 in /usr/local/lib/python3.10/dist-packages (from oauth2client>=4.0.0->PyDrive) (1.16.0)\n",
            "Requirement already satisfied: googleapis-common-protos<2.0.dev0,>=1.56.2 in /usr/local/lib/python3.10/dist-packages (from google-api-core!=2.0.*,!=2.1.*,!=2.2.*,!=2.3.0,<3.0.0.dev0,>=1.31.5->google-api-python-client>=1.2->PyDrive) (1.65.0)\n",
            "Requirement already satisfied: protobuf!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<6.0.0.dev0,>=3.19.5 in /usr/local/lib/python3.10/dist-packages (from google-api-core!=2.0.*,!=2.1.*,!=2.2.*,!=2.3.0,<3.0.0.dev0,>=1.31.5->google-api-python-client>=1.2->PyDrive) (3.20.3)\n",
            "Requirement already satisfied: proto-plus<2.0.0dev,>=1.22.3 in /usr/local/lib/python3.10/dist-packages (from google-api-core!=2.0.*,!=2.1.*,!=2.2.*,!=2.3.0,<3.0.0.dev0,>=1.31.5->google-api-python-client>=1.2->PyDrive) (1.24.0)\n",
            "Requirement already satisfied: requests<3.0.0.dev0,>=2.18.0 in /usr/local/lib/python3.10/dist-packages (from google-api-core!=2.0.*,!=2.1.*,!=2.2.*,!=2.3.0,<3.0.0.dev0,>=1.31.5->google-api-python-client>=1.2->PyDrive) (2.32.3)\n",
            "Requirement already satisfied: cachetools<6.0,>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from google-auth!=2.24.0,!=2.25.0,<3.0.0.dev0,>=1.32.0->google-api-python-client>=1.2->PyDrive) (5.5.0)\n",
            "Requirement already satisfied: pyparsing!=3.0.0,!=3.0.1,!=3.0.2,!=3.0.3,<4,>=2.4.2 in /usr/local/lib/python3.10/dist-packages (from httplib2<1.dev0,>=0.19.0->google-api-python-client>=1.2->PyDrive) (3.2.0)\n",
            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests<3.0.0.dev0,>=2.18.0->google-api-core!=2.0.*,!=2.1.*,!=2.2.*,!=2.3.0,<3.0.0.dev0,>=1.31.5->google-api-python-client>=1.2->PyDrive) (3.4.0)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests<3.0.0.dev0,>=2.18.0->google-api-core!=2.0.*,!=2.1.*,!=2.2.*,!=2.3.0,<3.0.0.dev0,>=1.31.5->google-api-python-client>=1.2->PyDrive) (3.10)\n",
            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests<3.0.0.dev0,>=2.18.0->google-api-core!=2.0.*,!=2.1.*,!=2.2.*,!=2.3.0,<3.0.0.dev0,>=1.31.5->google-api-python-client>=1.2->PyDrive) (2.2.3)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests<3.0.0.dev0,>=2.18.0->google-api-core!=2.0.*,!=2.1.*,!=2.2.*,!=2.3.0,<3.0.0.dev0,>=1.31.5->google-api-python-client>=1.2->PyDrive) (2024.8.30)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yZKLEChp4Tby"
      },
      "source": [
        "## Get .tar files, mount to Google Colab"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DbYtmf5MtSqI",
        "outputId": "4add8638-df85-4f9d-ba77-a1246c07d641",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "import os\n",
        "from pydrive.auth import GoogleAuth\n",
        "from pydrive.drive import GoogleDrive\n",
        "from google.colab import auth\n",
        "from oauth2client.client import GoogleCredentials\n",
        "\n",
        "# 1. Authenticate and create the PyDrive client.\n",
        "auth.authenticate_user()\n",
        "gauth = GoogleAuth()\n",
        "gauth.credentials = GoogleCredentials.get_application_default()\n",
        "drive = GoogleDrive(gauth)\n",
        "\n",
        "# choose a local (colab) directory to store the data.\n",
        "local_download_path = os.path.expanduser('./data')\n",
        "try:\n",
        "  os.makedirs(local_download_path)\n",
        "except: pass\n",
        "\n",
        "# 2. Auto-iterate using the query syntax\n",
        "#    https://developers.google.com/drive/v2/web/search-parameters\n",
        "file_list = drive.ListFile(\n",
        "    {'q': \"'1LOhNjbDUFMDxqWvzlaJeN2JVytuHEPzd' in parents\"}).GetList()\n",
        "\n",
        "for f in file_list:\n",
        "  # 3. Create & download by id.\n",
        "  print('title: %s, id: %s' % (f['title'], f['id']))\n",
        "  fname = os.path.join(local_download_path, f['title'])\n",
        "  print('downloading to {}'.format(fname))\n",
        "  f_ = drive.CreateFile({'id': f['id']})\n",
        "  f_.GetContentFile(fname)"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "WARNING:root:pydrive is deprecated and no longer maintained. We recommend that you migrate your projects to pydrive2, the maintained fork of pydrive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "iatajZNT4aDm"
      },
      "source": [
        "## Make meme video"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FccMfCNrbWt8"
      },
      "source": [
        "import imageio\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import matplotlib.animation as animation\n",
        "from skimage.transform import resize\n",
        "from IPython.display import HTML\n",
        "import warnings\n",
        "warnings.filterwarnings(\"ignore\")\n",
        "\n",
        "source_image = imageio.imread(\"./Fun_Cool_Sexy_Damedane/zyde.jpg\")\n",
        "driving_video = imageio.mimread(\"./Fun_Cool_Sexy_Damedane/dame_da_ne_source.mp4\")\n",
        "\n",
        "#Resize image and video to 256x256\n",
        "source_image = resize(source_image, (256, 256))[..., :3]\n",
        "driving_video = [resize(frame, (256, 256))[..., :3] for frame in driving_video]\n",
        "\n",
        "def display(source, driving, generated=None):\n",
        "    fig = plt.figure(figsize=(8 + 4 * (generated is not None), 6))\n",
        "\n",
        "    ims = []\n",
        "    for i in range(len(driving)):\n",
        "        cols = [source]\n",
        "        cols.append(driving[i])\n",
        "        if generated is not None:\n",
        "            cols.append(generated[i])\n",
        "        im = plt.imshow(np.concatenate(cols, axis=1), animated=True)\n",
        "        plt.axis('off')\n",
        "        ims.append([im])\n",
        "\n",
        "    ani = animation.ArtistAnimation(fig, ims, interval=50, repeat_delay=1000)\n",
        "    plt.close()\n",
        "    return ani\n",
        "\n",
        "\n",
        "HTML(display(source_image, driving_video).to_html5_video())"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SXwblT-GwSce"
      },
      "source": [
        "%cd first-order-model"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DzBJa_sAcHfJ"
      },
      "source": [
        "from demo import load_checkpoints\n",
        "generator, kp_detector = load_checkpoints(config_path='config/vox-256.yaml',\n",
        "                            checkpoint_path='../data/vox-cpk.pth.tar')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qaYXE7rYeFZt"
      },
      "source": [
        "from demo import make_animation\n",
        "from skimage import img_as_ubyte\n",
        "\n",
        "predictions = make_animation(source_image, driving_video, generator, kp_detector, relative=True)\n",
        "\n",
        "#save resulting video\n",
        "imageio.mimsave('../generated.mp4', [img_as_ubyte(frame) for frame in predictions])\n",
        "#video can be downloaded from /content folder\n",
        "\n",
        "HTML(display(source_image, driving_video, predictions).to_html5_video())"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "RyHf-F-Z4FfM"
      },
      "source": [
        "## Add music to mp4 file"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KBqRfybvhuhJ"
      },
      "source": [
        "! pip install imageio-ffmpeg moviepy"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sYDRWHPiiDlN"
      },
      "source": [
        "import warnings\n",
        "warnings.filterwarnings(\"ignore\")\n",
        "from moviepy.editor import VideoFileClip, vfx, AudioFileClip, CompositeAudioClip\n",
        "\n",
        "\n",
        "print('Speeding video up by 1.5x')\n",
        "import_path = '../generated.mp4'\n",
        "clip = VideoFileClip(import_path)\n",
        "finalclip = clip.fx(vfx.speedx, 3)\n",
        "\n",
        "print('Adding Background Music')\n",
        "audio = AudioFileClip('../Fun_Cool_Sexy_Damedane/audio.mp3')\n",
        "print('Exporting final clip')\n",
        "finalclip = finalclip.set_audio(audio)\n",
        "\n",
        "export_path = '../generated_with_sound.mp4'\n",
        "finalclip.write_videofile(export_path)\n",
        "print(f'video exported as {export_path}')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oAbl1RiCib_-"
      },
      "source": [],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "SFXplR92z3M_"
      },
      "source": [
        "### Download the meme from the left panel!\n",
        "\n",
        "![Screen Shot 2020-09-26 at 2.07.21 PM.png](data:image/png;base64,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)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0ZXdkCXD0Wft"
      },
      "source": [],
      "execution_count": null,
      "outputs": []
    }
  ]
}