Edit Video and Create Gifs using SOTA ASR.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "videoeditexperiment.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "authorship_tag": "ABX9TyNXxXQSghf3b/IojvEv4OZ/",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/yvrjsharma/HugginFace_Gradio/blob/main/Edit%20Video%20and%20Create%20Gifs%20using%20SOTA%20ASR.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install -q gradio\n",
        "!pip install ffmpeg"
      ],
      "metadata": {
        "id": "4_IiKIRw_8Ab"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#!pip uninstall ffmpeg\n",
        "!pip install ffmpeg-python"
      ],
      "metadata": {
        "id": "PGMV1y69MunE"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Run this cell to mount your Google Drive.\n",
        "from google.colab import drive\n",
        "drive.flush_and_unmount()\n",
        "drive.mount('/content/gdrive/')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-2Ml8kvOB45_",
        "outputId": "a5626df0-a7b5-4c07-a229-a6a879d71959"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Drive not mounted, so nothing to flush and unmount.\n",
            "Mounted at /content/gdrive/\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#done\n",
        "import gradio as gr\n",
        "import json\n",
        "from difflib import Differ\n",
        "import ffmpeg\n",
        "import os\n",
        "from pathlib import Path\n",
        "import time\n",
        "\n",
        "API_URL = \"https://api-inference.huggingface.co/models/facebook/wav2vec2-base-960h\"\n"
      ],
      "metadata": {
        "id": "9fK4N_P__734"
      },
      "execution_count": 95,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "import requests\n",
        "import base64\n",
        "import asyncio"
      ],
      "metadata": {
        "id": "GMXHPdGWAS3W"
      },
      "execution_count": 96,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#done\n",
        "videopath = \"/content/gdrive/My Drive/AI/videoedit/ShiaLaBeouf.mp4\""
      ],
      "metadata": {
        "id": "EKlPJLnkASxe"
      },
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#done\n",
        "video_path = Path(\"/content/gdrive/My Drive/AI/videoedit/ShiaLaBeouf.mp4\")\n",
        "video_path\n",
        "\n",
        "#VIDEOS =  \"/content/gdrive/My Drive/AI/videoedit/ShiaLaBeouf.mp4\""
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lzgL4A5rCybi",
        "outputId": "2db01c21-8013-450a-89b8-231928dd521c"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "PosixPath('/content/gdrive/My Drive/AI/videoedit/ShiaLaBeouf.mp4')"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#convert video to audio\n",
        "audio_memory, _ = ffmpeg.input(video_path).output('-', format=\"wav\", ac=1, ar='16k').overwrite_output().global_args('-loglevel', 'quiet').run(capture_stdout=True)"
      ],
      "metadata": {
        "id": "R5yr8lx0KyxD"
      },
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import ast\n",
        "# Converting string to list\n",
        "res = ast.literal_eval(a)\n",
        "len(res)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Ty118bsOm-OS",
        "outputId": "36b63983-ab0a-42d9-f82a-2a8f99765930"
      },
      "execution_count": 88,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "91"
            ]
          },
          "metadata": {},
          "execution_count": 88
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "a = \"\"\"['do', 'it', 'just', 'do', 'it', \"don't\", 'let', 'your', 'dreams', 'be', 'dreams', 'yesterday', 'you', 'said', 'to', 'morrow', 'so', 'just', 'do', 'it', 'make', 'you', 'dreams', \"can't\", 'yro', 'just', 'do', 'it', 'some', 'people', 'dream', 'of', 'success', 'while', \"you're\", 'going', 'to', 'wake', 'up', 'and', 'work', 'hot', 'ati', 'nothing', 'is', 'impossible', 'you', 'should', 'get', 'to', 'the', 'point', 'where', 'any', 'one', 'else', 'would', 'quit', 'and', \"you're\", 'luck', 'in', 'a', 'stop', 'there', 'no', 'what', 'are', 'you', 'waiting', 'for', 'do', 'et', 'jot', 'do', 'it', 'just', 'you', 'can', 'just', 'do', 'it', 'if', \"you're\", 'tired', 'is', 'starting', 'over', 'stop', 'giving', 'up']\"\"\"\n",
        "len(a)\n",
        "a[1:-1].split(',')"
      ],
      "metadata": {
        "id": "us1nzslgl5PE"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#final\n",
        "import gradio as gr\n",
        "#import json\n",
        "#from difflib import Differ\n",
        "import ffmpeg\n",
        "#import os\n",
        "from pathlib import Path\n",
        "#import time\n",
        "\n",
        "API_URL = \"https://api-inference.huggingface.co/models/facebook/wav2vec2-base-960h\"\n",
        "headers = {\"Authorization\": \"Bearer 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\"}\n",
        "\n",
        "#convert video to audio\n",
        "video_path = Path(\"/content/gdrive/My Drive/AI/videoedit/ShiaLaBeouf.mp4\")\n",
        "audio_memory, _ = ffmpeg.input(video_path).output('-', format=\"wav\", ac=1, ar='16k').overwrite_output().global_args('-loglevel', 'quiet').run(capture_stdout=True)\n",
        "\n",
        "#calling the hosted model\n",
        "def query_api(audio_bytes: bytes):\n",
        "    \"\"\"\n",
        "    Query for Huggingface Inference API for Automatic Speech Recognition task\n",
        "    \"\"\"\n",
        "    payload = json.dumps({\n",
        "        \"inputs\": base64.b64encode(audio_bytes).decode(\"utf-8\"),\n",
        "        \"parameters\": {\n",
        "            \"return_timestamps\": \"char\",\n",
        "            \"chunk_length_s\": 10,\n",
        "            \"stride_length_s\": [4, 2]\n",
        "        },\n",
        "        \"options\": {\"use_gpu\": False}\n",
        "    }).encode(\"utf-8\")\n",
        "\n",
        "    response = requests.request(\n",
        "        \"POST\", API_URL, headers=headers, data=payload)\n",
        "    json_reponse = json.loads(response.content.decode(\"utf-8\"))\n",
        "    return json_reponse\n",
        "\n",
        "#Getting transcripts using wav2Vec2 huggingface hosted accelerated inference\n",
        "#sending audio file in request along with stride and chunk length information\n",
        "model_response = query_api(audio_memory)\n",
        "\n",
        "#model response has both - transcripts as well as character timestamps or chunks\n",
        "transcription = model_response[\"text\"].lower()\n",
        "chnk = model_response[\"chunks\"]\n",
        "\n",
        "#creating lists from chunks to consume downstream easily\n",
        "timestamps = [[chunk[\"text\"].lower(), chunk[\"timestamp\"][0], chunk[\"timestamp\"][1]]\n",
        "          for chunk in chnk]\n",
        "\n",
        "\n",
        "#getting word timestams from character timestamps\n",
        "def get_word_timestamps(timestamps): \n",
        "  words, word = [], []\n",
        "  letter_timestamp, word_timestamp, words_timestamp = [], [], []\n",
        "  for idx,entry in enumerate(timestamps):\n",
        "    word.append(entry[0])\n",
        "    letter_timestamp.append(entry[1])\n",
        "    if entry[0] == ' ':\n",
        "      words.append(''.join(word))\n",
        "      word_timestamp.append(letter_timestamp[0])\n",
        "      word_timestamp.append(timestamps[idx-1][2])\n",
        "      words_timestamp.append(word_timestamp)\n",
        "      word, word_timestamp, letter_timestamp = [], [], []\n",
        "\n",
        "  words = [word.strip() for word in words]\n",
        "  return words, words_timestamp\n",
        "\n",
        "words, words_timestamp = get_word_timestamps(timestamps)\n",
        "#words = [word.strip() for word in words]\n",
        "\n",
        "print(f\"Total words in the audio transcript is:{len(words)}, transcript word list is :{words}\")\n",
        "print(f\"Total Word timestamps derived fromcharacter timestamp are :{len(words_timestamp)}, Word timestamps are :{words_timestamp}\")\n",
        "\n",
        "#creating list from input gif transcript \n",
        "gif = \"don't let your dreams be dreams\"\n",
        "giflist = gif.split()\n",
        "\n",
        "#getting index of gif words in main transcript\n",
        "def get_gif_word_indexes(total_words_list, gif_words_list):  \n",
        "    if not gif_words_list:\n",
        "        return\n",
        "    # just optimization\n",
        "    lengthgif_words_list = len(gif_words_list)\n",
        "    firstgif_words_list = gif_words_list[0]\n",
        "    for idx, item in enumerate(total_words_list):\n",
        "        if item == firstgif_words_list:\n",
        "            if total_words_list[idx:idx+lengthgif_words_list] == gif_words_list:\n",
        "                yield tuple(range(idx, idx+lengthgif_words_list))\n",
        "\n",
        "#getting gif indexes from the generator\n",
        "giflist_indxs = list(list(get_gif_word_indexes(words, giflist))[0])\n",
        "\n",
        "#getting start and end timestamps for gif transcript\n",
        "def get_gif_timestamps(giflist_indxs):\n",
        "  #giflist_indxs = list(list(get_gif_word_indexes(words, giflist))[0])\n",
        "  min_idx = min(giflist_indxs)\n",
        "  max_idx = max(giflist_indxs)\n",
        "\n",
        "  gif_words_timestamp = words_timestamp[min_idx : max_idx+1]\n",
        "  start_seconds, end_seconds = gif_words_timestamp[0][0], gif_words_timestamp[-1][-1]\n",
        "  return start_seconds, end_seconds\n",
        "\n",
        "#getting start and end timestamps for a gif video\n",
        "start_seconds, end_seconds = get_gif_timestamps(giflist_indxs)\n",
        "\n",
        "#extracting the  video and building and serving a .gif image\n",
        "def generate_gif(start_seconds, end_seconds):\n",
        "  final_clip = video.subclip(start_seconds, end_seconds)\n",
        "  #final_clip.write_videofile(\"/content/gdrive/My Drive/AI/videoedit/gif1.mp4\")\n",
        "  final_clip.write_gif(\"/content/gdrive/My Drive/AI/videoedit/gif1.gif\",)\n",
        "  final_clip.close()\n",
        "  return \n",
        "\n",
        "generate_gif(start_seconds, end_seconds)\n"
      ],
      "metadata": {
        "id": "o7gN4jVHKyrB"
      },
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from PIL import Image\n",
        "im = Image.open(\"/content/gdrive/My Drive/AI/videoedit/gif1.gif\")\n",
        "im"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AJknzgMs-B85",
        "outputId": "516537d8-53fa-444c-c094-0c41ba5a9881"
      },
      "execution_count": 76,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<PixelAccess at 0x7f14e0e0ce50>"
            ]
          },
          "metadata": {},
          "execution_count": 76
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#done\n",
        "transcription = query_api(audio_memory)[\"text\"].lower()\n",
        "transcription"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 72
        },
        "id": "rwe3Gn5jA5kY",
        "outputId": "6c9b958f-557e-413a-c664-9eae31c4a5af"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "\"do it just do it don't let your dreams be dreams yesterday you said to morrow so just do it make you dreams can't yro just do it some people dream of success while you're going to wake up and work hot ati nothing is impossible you should get to the point where any one else would quit and you're luck in a stop there no what are you waiting for do et jot do it just you can just do it if you're tired is starting over stop giving up\""
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "do it just do it don't let your dreams be dreams yesterday you said to morrow so just do it make you dreams can't yro just do it some people dream of success while you're going to wake up and work hot ati nothing is impossible you should get to the point where any one else would quit and you're luck in a stop there no what are you waiting for do et jot do it just you can just do it if you're tired is starting over stop giving up\n",
        "\n",
        "---------------\n",
        "do it just do it don't let your dreams be dreams yesterday you said tomorrow so just do it make your dreams come true just do it some people dream of success while you're going to wake up and work hard at it nothing is impossible you should get to the point where any one else would quit and you're not gonna stop there no what are you waiting for do it just do it yes you can just do it if you're tired of starting over stop giving up\n",
        "\n",
        "---------------\n",
        "don't do it just let your dreams be dreams do it tomorrow just do it tomorrow don't make your dreams come true just dont't just dream of success don't wake up and work hard at nothing it is impossible you should get to the point and quit and you're gonna stop there what are you waiting for just don't do it you can just don't do it you're tired stop starting over giving up"
      ],
      "metadata": {
        "id": "0gTjRVt4NuhP"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#done\n",
        "chnk = query_api(audio_memory)[\"chunks\"]\n",
        "query_api(audio_memory)[\"chunks\"][:24]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "sE2s7ymiU40k",
        "outputId": "46446b67-444f-4e11-846d-3b67a312d0e9"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[{'text': 'D', 'timestamp': [2.36, 2.38]},\n",
              " {'text': 'O', 'timestamp': [2.52, 2.56]},\n",
              " {'text': ' ', 'timestamp': [2.68, 2.72]},\n",
              " {'text': 'I', 'timestamp': [2.84, 2.86]},\n",
              " {'text': 'T', 'timestamp': [2.88, 2.92]},\n",
              " {'text': ' ', 'timestamp': [2.94, 2.98]},\n",
              " {'text': 'J', 'timestamp': [4.48, 4.52]},\n",
              " {'text': 'U', 'timestamp': [4.66, 4.68]},\n",
              " {'text': 'S', 'timestamp': [4.7, 4.74]},\n",
              " {'text': 'T', 'timestamp': [4.76, 4.78]},\n",
              " {'text': ' ', 'timestamp': [4.84, 4.88]},\n",
              " {'text': 'D', 'timestamp': [5.2, 5.22]},\n",
              " {'text': 'O', 'timestamp': [5.32, 5.36]},\n",
              " {'text': ' ', 'timestamp': [5.48, 5.52]},\n",
              " {'text': 'I', 'timestamp': [5.6, 5.62]},\n",
              " {'text': 'T', 'timestamp': [5.64, 5.66]},\n",
              " {'text': ' ', 'timestamp': [5.68, 5.74]},\n",
              " {'text': 'D', 'timestamp': [7.26, 7.28]},\n",
              " {'text': 'O', 'timestamp': [7.32, 7.34]},\n",
              " {'text': 'N', 'timestamp': [7.36, 7.42]},\n",
              " {'text': \"'\", 'timestamp': [7.42, 7.46]},\n",
              " {'text': 'T', 'timestamp': [7.46, 7.5]},\n",
              " {'text': ' ', 'timestamp': [7.5, 7.54]},\n",
              " {'text': 'L', 'timestamp': [7.58, 7.6]}]"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#nope\n",
        "#[['d', 2.36, 2.38],\n",
        "# ['o', 2.52, 2.56],\n",
        "#timestamps_dict = {entry[0]:[entry[1],entry[2]] for entry in timestamps}"
      ],
      "metadata": {
        "id": "MnwlUHnaPjty"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#not anymore\n",
        "timestamps_edit = [['delete', 11.64, 11.66  ],\n",
        "['r', 14.98, 15.0      ],\n",
        "['o', 15.86, 15.88     ],\n",
        "['m' , 15.9, 15.94     ],\n",
        "['e' , 15.96, 15.98    ],\n",
        "[' ', 15.98, 16.0      ],\n",
        "['t', 16.02, 16.06     ],\n",
        "['r', 16.1, 16.12      ],\n",
        "['u', 16.14, 16.16     ],\n",
        "['e', 16.3, 16.32      ],\n",
        "['a', 25.04, 25.06     ],\n",
        "['r' , 25.16, 25.18    ],\n",
        "['d' , 25.2, 25.22     ],\n",
        "['t' , 25.46, 25.5     ],\n",
        "['n', 33.26, 33.28     ],\n",
        "['o' , 33.34, 33.36    ],\n",
        "['t' , 33.36, 33.4     ],\n",
        "[' ', 33.42, 33.44     ],\n",
        "['g', 33.46, 33.48   ],\n",
        "['o', 33.52, 33.54    ],\n",
        "['n', 33.6, 33.64     ],\n",
        "[' ', 33.66, 33.72     ],\n",
        "['i', 38.66, 38.68    ],\n",
        "['u', 41.22, 41.24    ],\n",
        "['s', 41.32, 41.34    ],\n",
        "['t', 41.4, 41.42     ],\n",
        "['y', 44.18, 44.2     ],\n",
        "['e', 44.3, 44.32     ],\n",
        "[' ', 44.38, 44.4     ],\n",
        "['delete', 44.42, 44.46 ],\n",
        "['o', 52.46, 52.48  ],\n",
        "['f', 52.48, 52.5     ]]"
      ],
      "metadata": {
        "id": "p37dg94FJjJp"
      },
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "timestamps = [[chunk[\"text\"].lower(), chunk[\"timestamp\"][0], chunk[\"timestamp\"][1]]\n",
        "          for chunk in chnk]\n",
        "timestamps[0:10]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "aBOmBgooVNDj",
        "outputId": "20d180c6-369c-430a-8cf7-6f3005cc7cdc"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[['d', 2.36, 2.38],\n",
              " ['o', 2.52, 2.56],\n",
              " [' ', 2.68, 2.72],\n",
              " ['i', 2.84, 2.86],\n",
              " ['t', 2.88, 2.92],\n",
              " [' ', 2.94, 2.98],\n",
              " ['j', 4.48, 4.52],\n",
              " ['u', 4.66, 4.68],\n",
              " ['s', 4.7, 4.74],\n",
              " ['t', 4.76, 4.78]]"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#not anymore\n",
        "for entry in timestamps:\n",
        "  for editd_entry in timestamps_edit:\n",
        "    if entry[1] == editd_entry[1] and entry[2] == editd_entry[2]:\n",
        "      entry[0] = editd_entry[0]\n",
        "\n",
        "timestamps = [entry for entry in timestamps if entry[0]!='delete']\n",
        "timestamps"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7_zJaWGqP8LO",
        "outputId": "4419de9d-f643-4ab5-cc66-6989508ba941"
      },
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[['d', 2.36, 2.38],\n",
              " ['o', 2.52, 2.56],\n",
              " [' ', 2.68, 2.72],\n",
              " ['i', 2.84, 2.86],\n",
              " ['t', 2.88, 2.92],\n",
              " [' ', 2.94, 2.98],\n",
              " ['j', 4.48, 4.52],\n",
              " ['u', 4.66, 4.68],\n",
              " ['s', 4.7, 4.74],\n",
              " ['t', 4.76, 4.78],\n",
              " [' ', 4.84, 4.88],\n",
              " ['d', 5.2, 5.22],\n",
              " ['o', 5.32, 5.36],\n",
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              " ['n', 44.96, 44.98],\n",
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              " ['f', 52.48, 52.5],\n",
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              " ['t', 52.6, 52.62],\n",
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              " [' ', 52.9, 52.96],\n",
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              " ['p', 54.66, 54.68],\n",
              " [' ', 54.72, 54.78],\n",
              " ['g', 55.26, 55.28],\n",
              " ['i', 55.38, 55.4],\n",
              " ['v', 55.46, 55.48],\n",
              " ['i', 55.56, 55.58],\n",
              " ['n', 55.58, 55.6],\n",
              " ['g', 55.62, 55.64],\n",
              " [' ', 55.64, 55.76],\n",
              " ['u', 56.14, 56.16],\n",
              " ['p', 56.18, 56.22],\n",
              " [' ', 56.24, 56.28]]"
            ]
          },
          "metadata": {},
          "execution_count": 34
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#not anymore\n",
        "transcription_edit =  ''.join([entry[0] for entry in timestamps])\n",
        "print(transcription_edit) \n",
        "#transcription_edit2 = "
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 72
        },
        "id": "Z0f_KsffGcvw",
        "outputId": "5adfd946-ec5b-4d8b-ffe0-80bf3e6ef955"
      },
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "\"do it just do it don't let your dreams be dreams yesterday you said tomorrow so just do it make yourdreams come true just do it some people dream of success while you're going to wake up and work hardatitnothing is impossible you should get to the point where any one else would quit and you're not gonna stop there no what are you waiting for do it justdo it yes you can just do it if you're tired of starting over stop giving up \""
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#done\n",
        "#getting word timestams from character timestamps\n",
        "def get_word_timestamps(timestamps): \n",
        "  words, word = [], []\n",
        "  letter_timestamp, word_timestamp, words_timestamp = [], [], []\n",
        "  for idx,entry in enumerate(timestamps):\n",
        "    word.append(entry[0])\n",
        "    letter_timestamp.append(entry[1])\n",
        "    if entry[0] == ' ':\n",
        "      words.append(''.join(word))\n",
        "      word_timestamp.append(letter_timestamp[0])\n",
        "      word_timestamp.append(timestamps[idx-1][2])\n",
        "      words_timestamp.append(word_timestamp)\n",
        "      word, word_timestamp, letter_timestamp = [], [], []\n",
        "\n",
        "  words = [word.strip() for word in words]\n",
        "  return words, words_timestamp\n",
        "\n",
        "words, words_timestamp = get_word_timestamps(timestamps)\n",
        "#words = [word.strip() for word in words]\n",
        "\n",
        "print(len(words), words)\n",
        "print(len(words_timestamp), words_timestamp)\n",
        "\n",
        "\n",
        "gif = \"don't let your dreams be dreams\"\n",
        "\n",
        "#getting index of gif words in main transcript\n",
        "def get_gif_word_indexes(total_words_list, gif_words_list):  \n",
        "    if not gif_words_list:\n",
        "        return\n",
        "    # just optimization\n",
        "    lengthgif_words_list = len(gif_words_list)\n",
        "    firstgif_words_list = gif_words_list[0]\n",
        "    for idx, item in enumerate(total_words_list):\n",
        "        if item == firstgif_words_list:\n",
        "            if total_words_list[idx:idx+lengthgif_words_list] == gif_words_list:\n",
        "                yield tuple(range(idx, idx+lengthgif_words_list))\n",
        "\n",
        "#getting gif indexes from the generator\n",
        "giflist_indxs = list(list(get_gif_word_indexes(words, giflist))[0])\n",
        "\n",
        "#getting timestamps for gif words\n",
        "def get_gif_timestamps(giflist_indxs):\n",
        "  #giflist_indxs = list(list(get_gif_word_indexes(words, giflist))[0])\n",
        "  min_idx = min(giflist_indxs)\n",
        "  max_idx = max(giflist_indxs)\n",
        "\n",
        "  gif_words_timestamp = words_timestamp[min_idx : max_idx+1]\n",
        "  start_seconds, end_seconds = gif_words_timestamp[0][0], gif_words_timestamp[-1][-1]\n",
        "  return start_seconds, end_seconds\n",
        "\n",
        "#getting start and end timestamps for a gif video\n",
        "start_seconds, end_seconds = get_gif_timestamps(giflist_indxs)\n",
        "\n",
        "#extracting the  video and building and serving a .gif image\n",
        "def generate_gif(start_seconds, end_seconds):\n",
        "  final_clip = video.subclip(start_seconds, end_seconds)\n",
        "  #final_clip.write_videofile(\"/content/gdrive/My Drive/AI/videoedit/gif1.mp4\")\n",
        "  final_clip.write_gif(\"/content/gdrive/My Drive/AI/videoedit/gif1.gif\",)\n",
        "  final_clip.close()\n",
        "  return \n",
        "\n",
        "generate_gif(start_seconds, end_seconds)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TxpLX1_0BMqP",
        "outputId": "a3ab564d-2e40-4671-f260-7cce20cd02ae"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "91 ['do ', 'it ', 'just ', 'do ', 'it ', \"don't \", 'let ', 'your ', 'dreams ', 'be ', 'dreams ', 'yesterday ', 'you ', 'said ', 'to ', 'morrow ', 'so ', 'just ', 'do ', 'it ', 'make ', 'you ', 'dreams ', \"can't \", 'yro ', 'just ', 'do ', 'it ', 'some ', 'people ', 'dream ', 'of ', 'success ', 'while ', \"you're \", 'going ', 'to ', 'wake ', 'up ', 'and ', 'work ', 'hot ', 'ati ', 'nothing ', 'is ', 'impossible ', 'you ', 'should ', 'get ', 'to ', 'the ', 'point ', 'where ', 'any ', 'one ', 'else ', 'would ', 'quit ', 'and ', \"you're \", 'luck ', 'in ', 'a ', 'stop ', 'there ', 'no ', 'what ', 'are ', 'you ', 'waiting ', 'for ', 'do ', 'et ', 'jot ', 'do ', 'it ', 'just ', 'you ', 'can ', 'just ', 'do ', 'it ', 'if ', \"you're \", 'tired ', 'is ', 'starting ', 'over ', 'stop ', 'giving ', 'up ']\n",
            "91 [[2.36, 2.56], [2.84, 2.92], [4.48, 4.78], [5.2, 5.36], [5.6, 5.66], [7.26, 7.5], [7.58, 7.74], [7.82, 7.96], [8.0, 8.48], [8.6, 8.7], [8.82, 9.3], [10.32, 10.86], [11.16, 11.24], [11.34, 11.48], [11.56, 11.64], [11.68, 11.96], [12.26, 12.36], [12.54, 12.88], [13.4, 13.58], [13.78, 13.84], [14.34, 14.58], [14.82, 14.9], [15.02, 15.42], [15.76, 16.0], [16.1, 16.32], [17.06, 17.3], [18.04, 18.26], [18.5, 18.56], [21.64, 21.8], [21.84, 22.08], [22.16, 22.38], [22.44, 22.48], [22.54, 23.02], [23.3, 23.44], [23.48, 23.64], [23.66, 23.76], [23.78, 23.82], [23.86, 24.06], [24.18, 24.24], [24.5, 24.56], [24.64, 24.8], [24.9, 25.18], [25.28, 25.42], [25.8, 26.16], [26.26, 26.34], [26.42, 27.1], [29.42, 29.52], [29.62, 29.82], [29.86, 30.0], [30.04, 30.12], [30.16, 30.24], [30.32, 30.58], [31.1, 31.26], [31.42, 31.56], [31.7, 31.78], [31.88, 32.04], [32.12, 32.28], [32.38, 32.6], [32.88, 32.96], [33.0, 33.22], [33.26, 33.44], [33.52, 33.56], [33.64, 33.66], [33.74, 33.98], [34.08, 34.28], [35.38, 35.56], [35.74, 35.86], [35.88, 35.94], [35.98, 36.06], [36.1, 36.42], [36.52, 36.7], [38.22, 38.38], [38.66, 38.8], [41.06, 41.34], [42.96, 43.12], [43.4, 43.5], [44.18, 44.4], [44.48, 44.58], [44.68, 44.98], [46.02, 46.32], [46.48, 46.64], [46.8, 46.86], [51.78, 51.82], [51.88, 52.06], [52.1, 52.4], [52.46, 52.5], [52.56, 52.9], [53.0, 53.2], [54.34, 54.68], [55.26, 55.64], [56.14, 56.22]]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#old\n",
        "words, word = [], []\n",
        "letter_timestamp, word_timestamp, words_timestamp = [], [], []\n",
        "for idx,entry in enumerate(timestamps):\n",
        "  word.append(entry[0])\n",
        "  letter_timestamp.append(entry[1])\n",
        "  if entry[0] == ' ':\n",
        "    words.append(''.join(word))\n",
        "    word_timestamp.append(letter_timestamp[0])\n",
        "    word_timestamp.append(timestamps[idx-1][2])\n",
        "    words_timestamp.append(word_timestamp)\n",
        "    word, word_timestamp, letter_timestamp = [], [], []\n",
        "print(len(words), words)\n",
        "print(len(words_timestamp), words_timestamp)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "APJPT0LaJPpG",
        "outputId": "a2b4ba28-b8e5-4349-82d3-81beb415b4fb"
      },
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "85 ['do ', 'it ', 'just ', 'do ', 'it ', \"don't \", 'let ', 'your ', 'dreams ', 'be ', 'dreams ', 'yesterday ', 'you ', 'said ', 'tomorrow ', 'so ', 'just ', 'do ', 'it ', 'make ', 'yourdreams ', 'come ', 'true ', 'just ', 'do ', 'it ', 'some ', 'people ', 'dream ', 'of ', 'success ', 'while ', \"you're \", 'going ', 'to ', 'wake ', 'up ', 'and ', 'work ', 'hardatitnothing ', 'is ', 'impossible ', 'you ', 'should ', 'get ', 'to ', 'the ', 'point ', 'where ', 'any ', 'one ', 'else ', 'would ', 'quit ', 'and ', \"you're \", 'not ', 'gonna ', 'stop ', 'there ', 'no ', 'what ', 'are ', 'you ', 'waiting ', 'for ', 'do ', 'it ', 'justdo ', 'it ', 'yes ', 'you ', 'can ', 'just ', 'do ', 'it ', 'if ', \"you're \", 'tired ', 'of ', 'starting ', 'over ', 'stop ', 'giving ', 'up ']\n",
            "85 [[2.36, 2.56], [2.84, 2.92], [4.48, 4.78], [5.2, 5.36], [5.6, 5.66], [7.26, 7.5], [7.58, 7.74], [7.82, 7.96], [8.0, 8.48], [8.6, 8.7], [8.82, 9.3], [10.32, 10.86], [11.16, 11.24], [11.34, 11.48], [11.56, 11.96], [12.26, 12.36], [12.54, 12.88], [13.4, 13.58], [13.78, 13.84], [14.34, 14.58], [14.82, 15.42], [15.76, 15.98], [16.02, 16.32], [17.06, 17.3], [18.04, 18.26], [18.5, 18.56], [21.64, 21.8], [21.84, 22.08], [22.16, 22.38], [22.44, 22.48], [22.54, 23.02], [23.3, 23.44], [23.48, 23.64], [23.66, 23.76], [23.78, 23.82], [23.86, 24.06], [24.18, 24.24], [24.5, 24.56], [24.64, 24.8], [24.9, 26.16], [26.26, 26.34], [26.42, 27.1], [29.42, 29.52], [29.62, 29.82], [29.86, 30.0], [30.04, 30.12], [30.16, 30.24], [30.32, 30.58], [31.1, 31.26], [31.42, 31.56], [31.7, 31.78], [31.88, 32.04], [32.12, 32.28], [32.38, 32.6], [32.88, 32.96], [33.0, 33.22], [33.26, 33.4], [33.46, 33.66], [33.74, 33.98], [34.08, 34.28], [35.38, 35.56], [35.74, 35.86], [35.88, 35.94], [35.98, 36.06], [36.1, 36.42], [36.52, 36.7], [38.22, 38.38], [38.66, 38.8], [41.06, 43.12], [43.4, 43.5], [44.18, 44.36], [44.48, 44.58], [44.68, 44.98], [46.02, 46.32], [46.48, 46.64], [46.8, 46.86], [51.78, 51.82], [51.88, 52.06], [52.1, 52.4], [52.46, 52.5], [52.56, 52.9], [53.0, 53.2], [54.34, 54.68], [55.26, 55.64], [56.14, 56.22]]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#no\n",
        "#video_path = Path(video_in)\n",
        "video_file_name = video_path.stem\n",
        "video_file_name\n",
        "\n",
        "video_file = ffmpeg.input(video_path)\n",
        "video_file\n",
        "\n",
        "video = video_file.video.filter(\"select\", 'd').filter(\"setpts\", \"N/FRAME_RATE/TB\")\n",
        "video\n",
        "\n",
        "audio = video_file.audio.filter(\"aselect\", 'd').filter(\"asetpts\", \"N/SR/TB\")\n",
        "audio\n",
        "\n",
        "output_video = f'./outvid.mp4'\n",
        "output_video = f\"/content/gdrive/My Drive/AI/videoedit/out1.mp4\"\n",
        "\n",
        "out = ffmpeg.output(video, audio, \"/content/gdrive/My Drive/AI/videoedit/out1.mp4\")\n",
        "out.run()\n",
        "\n",
        "#video = video_file.video.filter(\"select\", f'({between_str})').filter(\"setpts\", \"N/FRAME_RATE/TB\")\n",
        "#audio = video_file.audio.filter(\"aselect\", f'({between_str})').filter(\"asetpts\", \"N/SR/TB\")\n",
        "\n",
        "#output_video = f'./videos_out/{video_file_name}.mp4'\n",
        "ffmpeg.concat(video, audio, v=1, a=1).output(output_video).run(overwrite_output=True) #overwrite_output().global_args('-loglevel', 'quiet') # .run()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 36
        },
        "id": "J4QHPvYYWVN7",
        "outputId": "3be4f89a-42d0-4e57-9cd5-1193628dbeaa"
      },
      "execution_count": 44,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'ShiaLaBeouf'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 44
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#new approach\n",
        "!pip install moviepy\n",
        "#import moviepy\n",
        "import moviepy.editor as mp\n",
        "video = mp.VideoFileClip(videopath)"
      ],
      "metadata": {
        "id": "_uayP8RWAHkv"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#no\n",
        "from moviepy.video.io.ffmpeg_tools import ffmpeg_extract_subclip\n",
        "ffmpeg_extract_subclip(videopath, 2, 15, targetname=\"/content/gdrive/My Drive/AI/videoedit/test.mp4\")  #videopath = \"/content/gdrive/My Drive/AI/videoedit/ShiaLaBeouf.mp4\"\n",
        "\n",
        "#no\n",
        "import moviepy.editor as mp\n",
        "\n",
        "video = mp.VideoFileClip(videopath)\n",
        "video.subclip(2, 3).write_videofile(\"/content/gdrive/My Drive/AI/videoedit/test1.mp4\")\n",
        "\n",
        "video.subclip(7.26, 7.5).write_videofile(\"/content/gdrive/My Drive/AI/videoedit/test2.mp4\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IsZH-BpI_CK1",
        "outputId": "0117cf65-c97e-47a7-c6e8-14883c244669"
      },
      "execution_count": 90,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "[MoviePy] Running:\n",
            ">>> /usr/bin/ffmpeg -y -i /content/gdrive/My Drive/AI/videoedit/ShiaLaBeouf.mp4 -ss 2.00 -t 13.00 -vcodec copy -acodec copy /content/gdrive/My Drive/AI/videoedit/test.mp4\n",
            "... command successful.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(len(words), words)\n",
        "print(len(words_timestamp), words_timestamp)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_hKFAFtQgBBT",
        "outputId": "60abd35c-4d4f-4d3d-d5d2-eb5873af27a7"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "91 ['do ', 'it ', 'just ', 'do ', 'it ', \"don't \", 'let ', 'your ', 'dreams ', 'be ', 'dreams ', 'yesterday ', 'you ', 'said ', 'to ', 'morrow ', 'so ', 'just ', 'do ', 'it ', 'make ', 'you ', 'dreams ', \"can't \", 'yro ', 'just ', 'do ', 'it ', 'some ', 'people ', 'dream ', 'of ', 'success ', 'while ', \"you're \", 'going ', 'to ', 'wake ', 'up ', 'and ', 'work ', 'hot ', 'ati ', 'nothing ', 'is ', 'impossible ', 'you ', 'should ', 'get ', 'to ', 'the ', 'point ', 'where ', 'any ', 'one ', 'else ', 'would ', 'quit ', 'and ', \"you're \", 'luck ', 'in ', 'a ', 'stop ', 'there ', 'no ', 'what ', 'are ', 'you ', 'waiting ', 'for ', 'do ', 'et ', 'jot ', 'do ', 'it ', 'just ', 'you ', 'can ', 'just ', 'do ', 'it ', 'if ', \"you're \", 'tired ', 'is ', 'starting ', 'over ', 'stop ', 'giving ', 'up ']\n",
            "91 [[2.36, 2.56], [2.84, 2.92], [4.48, 4.78], [5.2, 5.36], [5.6, 5.66], [7.26, 7.5], [7.58, 7.74], [7.82, 7.96], [8.0, 8.48], [8.6, 8.7], [8.82, 9.3], [10.32, 10.86], [11.16, 11.24], [11.34, 11.48], [11.56, 11.64], [11.68, 11.96], [12.26, 12.36], [12.54, 12.88], [13.4, 13.58], [13.78, 13.84], [14.34, 14.58], [14.82, 14.9], [15.02, 15.42], [15.76, 16.0], [16.1, 16.32], [17.06, 17.3], [18.04, 18.26], [18.5, 18.56], [21.64, 21.8], [21.84, 22.08], [22.16, 22.38], [22.44, 22.48], [22.54, 23.02], [23.3, 23.44], [23.48, 23.64], [23.66, 23.76], [23.78, 23.82], [23.86, 24.06], [24.18, 24.24], [24.5, 24.56], [24.64, 24.8], [24.9, 25.18], [25.28, 25.42], [25.8, 26.16], [26.26, 26.34], [26.42, 27.1], [29.42, 29.52], [29.62, 29.82], [29.86, 30.0], [30.04, 30.12], [30.16, 30.24], [30.32, 30.58], [31.1, 31.26], [31.42, 31.56], [31.7, 31.78], [31.88, 32.04], [32.12, 32.28], [32.38, 32.6], [32.88, 32.96], [33.0, 33.22], [33.26, 33.44], [33.52, 33.56], [33.64, 33.66], [33.74, 33.98], [34.08, 34.28], [35.38, 35.56], [35.74, 35.86], [35.88, 35.94], [35.98, 36.06], [36.1, 36.42], [36.52, 36.7], [38.22, 38.38], [38.66, 38.8], [41.06, 41.34], [42.96, 43.12], [43.4, 43.5], [44.18, 44.4], [44.48, 44.58], [44.68, 44.98], [46.02, 46.32], [46.48, 46.64], [46.8, 46.86], [51.78, 51.82], [51.88, 52.06], [52.1, 52.4], [52.46, 52.5], [52.56, 52.9], [53.0, 53.2], [54.34, 54.68], [55.26, 55.64], [56.14, 56.22]]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "gif = \"don't let your dreams be dreams\""
      ],
      "metadata": {
        "id": "AX5uuRBCIlnJ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "words = [word.strip() for word in words]"
      ],
      "metadata": {
        "id": "D8fnY8C7u6rY"
      },
      "execution_count": 18,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#no\n",
        "import random\n",
        "\n",
        "def make_gif(fun, name):\n",
        "  funlist = fun.split()\n",
        "  fundict = {}\n",
        "  for in_word in funlist:\n",
        "    fundict[in_word] = [idx for idx, word in enumerate(words) if word == in_word]\n",
        "  fundict_new = {item[0]: random.choice(item[1]) for item in fundict.items() if len(item[1]) !=0 }\n",
        "  funlist_indxs = [ fundict_new[word] for word in funlist if word in list(fundict_new.keys()) ]\n",
        "  funlist_indxs_timestmp = [words_timestamp[idx] for idx in funlist_indxs]\n",
        "  clips = []  # list of all video fragments\n",
        "  for start_seconds, end_seconds in funlist_indxs_timestmp:\n",
        "      # crop a video clip and add it to list\n",
        "      c = video.subclip(start_seconds, end_seconds)\n",
        "      clips.append(c)\n",
        "\n",
        "  final_clip = mp.concatenate_videoclips(clips)\n",
        "  filename = f'{name}.mp4'\n",
        "  final_clip.write_videofile(f\"/content/gdrive/My Drive/AI/videoedit/{filename}\")\n",
        "  final_clip.close()\n",
        "  return"
      ],
      "metadata": {
        "id": "jCO60XiNCIjC"
      },
      "execution_count": 23,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#no\n",
        "import moviepy.editor as mp\n",
        "\n",
        "clips = []  # list of all video fragments\n",
        "for start_seconds, end_seconds in funlist_indxs_timestmp:\n",
        "  # crop a video clip and add it to list\n",
        "  c = video.subclip(start_seconds, end_seconds)\n",
        "  clips.append(c)"
      ],
      "metadata": {
        "id": "lMpno01cVS1h"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "make_gif(gif,'fun15')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Mf3qyElZEhmt",
        "outputId": "ce8afbe9-d379-474e-f496-71fe36f8f71d"
      },
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[MoviePy] >>>> Building video /content/gdrive/My Drive/AI/videoedit/fun15.mp4\n",
            "[MoviePy] Writing audio in fun15TEMP_MPY_wvf_snd.mp3\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|██████████| 32/32 [00:00<00:00, 200.80it/s]"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[MoviePy] Done.\n",
            "[MoviePy] Writing video /content/gdrive/My Drive/AI/videoedit/fun15.mp4\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\n",
            "100%|██████████| 35/35 [00:00<00:00, 52.04it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[MoviePy] Done.\n",
            "[MoviePy] >>>> Video ready: /content/gdrive/My Drive/AI/videoedit/fun15.mp4 \n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#no\n",
        "from moviepy.editor import VideoFileClip\n",
        "videoClip = VideoFileClip(\"my-life.mp4\")\n",
        "videoClip.write_gif(\"my-life.gif\")"
      ],
      "metadata": {
        "id": "J6GnpaQQH0Xs"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "do it just do it don't let your dreams be dreams yesterday you said tomorrow so just do it make yourdreams come true just do it some people dream of success while you're going to wake up and work hardatitnothing is impossible you should get to the point where any one else would quit and you're not gonna stop there no what are you waiting for do it justdo it yes you can just do it if you're tired of starting over stop giving up "
      ],
      "metadata": {
        "id": "y0To08o8FM6i"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "gif = \"don't let your dreams be dreams\""
      ],
      "metadata": {
        "id": "M4gh2LJlFT23"
      },
      "execution_count": 21,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#old\n",
        "fun = \"don't do it just let your dreams be dreams do it tomorrow just do it tomorrow don't make your dreams come true just dont't just dream of success don't wake up and work hard at nothing it is impossible you should get to the point and quit and you're gonna stop there what are you waiting for just don't do it you can just don't do it you're tired stop starting over giving up\"\n",
        "display(fun)\n",
        "fun = \"just let your dreams be dreams\"\n",
        "fun = \"don't make your dreams come true\"\n",
        "fun = \"just dream of success don't wake up and work\"\n",
        "fun = \"it is impossible\"\n",
        "fun = \"you're tired\"\n",
        "fun = \"dreams do come true don't quit\"\n",
        "fun = \"dreams do come true don't quit dreams do come true don't quit dreams do come true don't quit don't let your dreams be dreams don't let your dreams be dreams don't let your dreams be dreams just do it do it\""
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 54
        },
        "id": "hnR06n7Pte7d",
        "outputId": "c854417b-872a-4b45-e5f6-627698583f2b"
      },
      "execution_count": 191,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "\"don't do it just let your dreams be dreams do it tomorrow just do it tomorrow don't make your dreams come true just dont't just dream of success don't wake up and work hard at nothing it is impossible you should get to the point and quit and you're gonna stop there what are you waiting for just don't do it you can just don't do it you're tired stop starting over giving up\""
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#funlist = fun.split()\n",
        "#print(funlist)\n",
        "giflist = gif.split()\n",
        "print(giflist)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5IFU_KaZt0Mc",
        "outputId": "bc3c12b1-2e71-4288-d0d6-76aabf216d80"
      },
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[\"don't\", 'let', 'your', 'dreams', 'be', 'dreams']\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(len(words), words)\n",
        "print(len(words_timestamp), words_timestamp)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "SfA5ojevKZ_N",
        "outputId": "c40a5e1d-f205-43ec-bb5d-9126508ea8ef"
      },
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "91 ['do', 'it', 'just', 'do', 'it', \"don't\", 'let', 'your', 'dreams', 'be', 'dreams', 'yesterday', 'you', 'said', 'to', 'morrow', 'so', 'just', 'do', 'it', 'make', 'you', 'dreams', \"can't\", 'yro', 'just', 'do', 'it', 'some', 'people', 'dream', 'of', 'success', 'while', \"you're\", 'going', 'to', 'wake', 'up', 'and', 'work', 'hot', 'ati', 'nothing', 'is', 'impossible', 'you', 'should', 'get', 'to', 'the', 'point', 'where', 'any', 'one', 'else', 'would', 'quit', 'and', \"you're\", 'luck', 'in', 'a', 'stop', 'there', 'no', 'what', 'are', 'you', 'waiting', 'for', 'do', 'et', 'jot', 'do', 'it', 'just', 'you', 'can', 'just', 'do', 'it', 'if', \"you're\", 'tired', 'is', 'starting', 'over', 'stop', 'giving', 'up']\n",
            "91 [[2.36, 2.56], [2.84, 2.92], [4.48, 4.78], [5.2, 5.36], [5.6, 5.66], [7.26, 7.5], [7.58, 7.74], [7.82, 7.96], [8.0, 8.48], [8.6, 8.7], [8.82, 9.3], [10.32, 10.86], [11.16, 11.24], [11.34, 11.48], [11.56, 11.64], [11.68, 11.96], [12.26, 12.36], [12.54, 12.88], [13.4, 13.58], [13.78, 13.84], [14.34, 14.58], [14.82, 14.9], [15.02, 15.42], [15.76, 16.0], [16.1, 16.32], [17.06, 17.3], [18.04, 18.26], [18.5, 18.56], [21.64, 21.8], [21.84, 22.08], [22.16, 22.38], [22.44, 22.48], [22.54, 23.02], [23.3, 23.44], [23.48, 23.64], [23.66, 23.76], [23.78, 23.82], [23.86, 24.06], [24.18, 24.24], [24.5, 24.56], [24.64, 24.8], [24.9, 25.18], [25.28, 25.42], [25.8, 26.16], [26.26, 26.34], [26.42, 27.1], [29.42, 29.52], [29.62, 29.82], [29.86, 30.0], [30.04, 30.12], [30.16, 30.24], [30.32, 30.58], [31.1, 31.26], [31.42, 31.56], [31.7, 31.78], [31.88, 32.04], [32.12, 32.28], [32.38, 32.6], [32.88, 32.96], [33.0, 33.22], [33.26, 33.44], [33.52, 33.56], [33.64, 33.66], [33.74, 33.98], [34.08, 34.28], [35.38, 35.56], [35.74, 35.86], [35.88, 35.94], [35.98, 36.06], [36.1, 36.42], [36.52, 36.7], [38.22, 38.38], [38.66, 38.8], [41.06, 41.34], [42.96, 43.12], [43.4, 43.5], [44.18, 44.4], [44.48, 44.58], [44.68, 44.98], [46.02, 46.32], [46.48, 46.64], [46.8, 46.86], [51.78, 51.82], [51.88, 52.06], [52.1, 52.4], [52.46, 52.5], [52.56, 52.9], [53.0, 53.2], [54.34, 54.68], [55.26, 55.64], [56.14, 56.22]]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#result = all(elem in big for elem in small)\n",
        "#all(elem in words for elem in giflist)\n",
        "def func(haystack, needle):  # obviously needs a better name ...\n",
        "    if not needle:\n",
        "        return\n",
        "    # just optimization\n",
        "    lengthneedle = len(needle)\n",
        "    firstneedle = needle[0]\n",
        "    for idx, item in enumerate(haystack):\n",
        "        if item == firstneedle:\n",
        "            if haystack[idx:idx+lengthneedle] == needle:\n",
        "                yield tuple(range(idx, idx+lengthneedle))\n",
        "\n",
        "giflist_indxs = list(list(func(words, giflist))[0]        )\n",
        "print(giflist_indxs)\n",
        "min_idx = min(giflist_indxs)\n",
        "max_idx = max(giflist_indxs)\n",
        "min_idx, max_idx"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YRLMCA7VcG_P",
        "outputId": "c786b217-89ab-4c59-fdf8-2730993b32f6"
      },
      "execution_count": 71,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[5, 6, 7, 8, 9, 10]\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(5, 10)"
            ]
          },
          "metadata": {},
          "execution_count": 71
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "gif_words_timestamp = words_timestamp[min_idx : max_idx+1]\n",
        "start_seconds, end_seconds = gif_words_timestamp[0][0], gif_words_timestamp[-1][-1]\n",
        "start_seconds, end_seconds"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LWA4i7l0lB0R",
        "outputId": "8ffbba93-2537-4602-e4cb-0b2856c2fc7a"
      },
      "execution_count": 73,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(7.26, 9.3)"
            ]
          },
          "metadata": {},
          "execution_count": 73
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#new approach\n",
        "!pip install moviepy\n",
        "#import moviepy\n",
        "import moviepy.editor as mp\n",
        "video = mp.VideoFileClip(videopath)"
      ],
      "metadata": {
        "id": "1gjt4PvlrvVr"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "gif = \"don't let your dreams be dreams\"\n",
        "\n",
        "def get_gif_word_indexes(total_words_list, gif_words_list):  \n",
        "    if not gif_words_list:\n",
        "        return\n",
        "    # just optimization\n",
        "    lengthgif_words_list = len(gif_words_list)\n",
        "    firstgif_words_list = gif_words_list[0]\n",
        "    for idx, item in enumerate(total_words_list):\n",
        "        if item == firstgif_words_list:\n",
        "            if total_words_list[idx:idx+lengthgif_words_list] == gif_words_list:\n",
        "                yield tuple(range(idx, idx+lengthgif_words_list))\n",
        "\n",
        "giflist_indxs = list(list(get_gif_word_indexes(words, giflist))[0])\n",
        "\n",
        "def get_gif_timestamps(giflist_indxs):\n",
        "  #giflist_indxs = list(list(get_gif_word_indexes(words, giflist))[0])\n",
        "  min_idx = min(giflist_indxs)\n",
        "  max_idx = max(giflist_indxs)\n",
        "\n",
        "  gif_words_timestamp = words_timestamp[min_idx : max_idx+1]\n",
        "  start_seconds, end_seconds = gif_words_timestamp[0][0], gif_words_timestamp[-1][-1]\n",
        "  return start_seconds, end_seconds\n",
        "\n",
        "start_seconds, end_seconds = get_gif_timestamps(giflist_indxs)\n",
        "\n",
        "def generate_gif(start_seconds, end_seconds):\n",
        "  final_clip = video.subclip(start_seconds, end_seconds)\n",
        "  #final_clip.write_videofile(\"/content/gdrive/My Drive/AI/videoedit/gif1.mp4\")\n",
        "  final_clip.write_gif(\"/content/gdrive/My Drive/AI/videoedit/gif1.gif\",)\n",
        "  final_clip.close()\n",
        "  return \n",
        "\n",
        "generate_gif(start_seconds, end_seconds)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wl5-arIml67I",
        "outputId": "95ce629c-2a05-487e-9fa3-d396144a9a0b"
      },
      "execution_count": 74,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[MoviePy] >>>> Building video /content/gdrive/My Drive/AI/videoedit/gif1.mp4\n",
            "[MoviePy] Writing audio in gif1TEMP_MPY_wvf_snd.mp3\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|██████████| 45/45 [00:00<00:00, 538.24it/s]"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[MoviePy] Done.\n",
            "[MoviePy] Writing video /content/gdrive/My Drive/AI/videoedit/gif1.mp4\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\n",
            "100%|██████████| 49/49 [00:00<00:00, 257.62it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[MoviePy] Done.\n",
            "[MoviePy] >>>> Video ready: /content/gdrive/My Drive/AI/videoedit/gif1.mp4 \n",
            "\n",
            "\n",
            "[MoviePy] Building file /content/gdrive/My Drive/AI/videoedit/gif1.gif with imageio\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|██████████| 49/49 [00:03<00:00, 14.80it/s]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "clips = []  # list of all video fragments\n",
        "for start_seconds, end_seconds in giflist_indxs_timestmp: #funlist_indxs_timestmp:\n",
        "    # crop a video clip and add it to list\n",
        "    c = video.subclip(start_seconds, end_seconds)\n",
        "    clips.append(c)\n",
        "\n",
        "final_clip = mp.concatenate_videoclips(clips)\n",
        "final_clip.write_videofile(\"/content/gdrive/My Drive/AI/videoedit/gif1.mp4\")\n",
        "final_clip.write_gif(\"/content/gdrive/My Drive/AI/videoedit/gif1.gif\")\n",
        "final_clip.close()"
      ],
      "metadata": {
        "id": "QdguxLrQkuWA"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "transcription"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 72
        },
        "id": "TNClymd2OsgR",
        "outputId": "12d19f67-3fe0-4067-8ffe-e5bdd2399dac"
      },
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "\"do it just do it don't let your dreams be dreams yesterday you said to morrow so just do it make you dreams can't yro just do it some people dream of success while you're going to wake up and work hot ati nothing is impossible you should get to the point where any one else would quit and you're luck in a stop there no what are you waiting for do et jot do it just you can just do it if you're tired is starting over stop giving up\""
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 39
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#new but no\n",
        "gifdict = {}\n",
        "for in_word in giflist:\n",
        "  gifdict[in_word] = [idx for idx, word in enumerate(words) if word == in_word]\n",
        "\n",
        "gifdict"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ItxPP5xYKTom",
        "outputId": "33350156-7d2c-43ef-9916-8578d3d21c66"
      },
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'be': [9], \"don't\": [5], 'dreams': [8, 10, 22], 'let': [6], 'your': [7]}"
            ]
          },
          "metadata": {},
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#new but no\n",
        "gifdict_new = {item[0]:min(item[1]) for item in gifdict.items() if len(item[1]) !=0 }\n",
        "gifdict_new"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EKUkMJFvSah7",
        "outputId": "b781b303-7a67-4c77-c94e-8f785471e73c"
      },
      "execution_count": 38,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'be': 9, \"don't\": 5, 'dreams': 8, 'let': 6, 'your': 7}"
            ]
          },
          "metadata": {},
          "execution_count": 38
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#new but no\n",
        "min_idx = min(list(gifdict_new.values()))\n",
        "max_idx = max(list(gifdict_new.values()))\n",
        "min_idx, max_idx"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8Gf8k50EUrjb",
        "outputId": "f947f128-e545-415f-d857-e3ee25834b2a"
      },
      "execution_count": 44,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(5, 9)"
            ]
          },
          "metadata": {},
          "execution_count": 44
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#old\n",
        "fundict = {}\n",
        "for in_word in funlist:\n",
        "  fundict[in_word] = [idx for idx, word in enumerate(words) if word == in_word]\n",
        "\n",
        "fundict"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "CLVSfGnewQ5d",
        "outputId": "7517d961-a48c-4c11-9fdc-3c561144b438"
      },
      "execution_count": 185,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'be': [9],\n",
              " 'come': [21],\n",
              " 'do': [0, 3, 17, 24, 66, 74],\n",
              " \"don't\": [5],\n",
              " 'dreams': [8, 10],\n",
              " 'let': [6],\n",
              " 'people': [27],\n",
              " 'quit': [53],\n",
              " 'true': [22],\n",
              " 'your': [7]}"
            ]
          },
          "metadata": {},
          "execution_count": 185
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#old\n",
        "import random\n",
        "fundict_new = {item[0]: random.choice(item[1]) for item in fundict.items() if len(item[1]) !=0 }\n",
        "fundict_new"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mN7iUh94yK4_",
        "outputId": "4b166fdc-1655-4b37-b12c-8a3427c14602"
      },
      "execution_count": 186,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'be': 9,\n",
              " 'come': 21,\n",
              " 'do': 17,\n",
              " \"don't\": 5,\n",
              " 'dreams': 10,\n",
              " 'let': 6,\n",
              " 'people': 27,\n",
              " 'quit': 53,\n",
              " 'true': 22,\n",
              " 'your': 7}"
            ]
          },
          "metadata": {},
          "execution_count": 186
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#old\n",
        "funlist_indxs = [ fundict_new[word] for word in funlist if word in list(fundict_new.keys()) ]\n",
        "funlist_indxs"
      ],
      "metadata": {
        "id": "VyJ2WIUp0WBk"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#new but no\n",
        "giflist_indxs_timestmp = [words_timestamp[idx] for idx in range(min_idx,max_idx+1)]\n",
        "giflist_indxs_timestmp"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xaltG8dJV1DM",
        "outputId": "0dba29d8-fe30-444e-bf0d-e218ec38a5a1"
      },
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[[7.26, 7.5], [7.58, 7.74], [7.82, 7.96], [8.0, 8.48], [8.6, 8.7]]"
            ]
          },
          "metadata": {},
          "execution_count": 45
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#old\n",
        "funlist_indxs_timestmp = [words_timestamp[idx] for idx in funlist_indxs]\n",
        "funlist_indxs_timestmp"
      ],
      "metadata": {
        "id": "PLbBCJ863TRQ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "clips = []  # list of all video fragments\n",
        "for start_seconds, end_seconds in giflist_indxs_timestmp: #funlist_indxs_timestmp:\n",
        "    # crop a video clip and add it to list\n",
        "    c = video.subclip(start_seconds, end_seconds)\n",
        "    clips.append(c)\n",
        "\n",
        "final_clip = mp.concatenate_videoclips(clips)\n",
        "final_clip.write_videofile(\"/content/gdrive/My Drive/AI/videoedit/gif1.mp4\")\n",
        "final_clip.write_gif(\"/content/gdrive/My Drive/AI/videoedit/gif1.gif\")\n",
        "final_clip.close()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Pja-omjN4NXC",
        "outputId": "3bf95490-e3d5-4dc1-dade-8b19f98fe7b3"
      },
      "execution_count": 66,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[MoviePy] >>>> Building video /content/gdrive/My Drive/AI/videoedit/gif1.mp4\n",
            "[MoviePy] Writing audio in gif1TEMP_MPY_wvf_snd.mp3\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|██████████| 36/36 [00:00<00:00, 494.24it/s]"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[MoviePy] Done.\n",
            "[MoviePy] Writing video /content/gdrive/My Drive/AI/videoedit/gif1.mp4\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\n",
            "100%|██████████| 39/39 [00:00<00:00, 237.43it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[MoviePy] Done.\n",
            "[MoviePy] >>>> Video ready: /content/gdrive/My Drive/AI/videoedit/gif1.mp4 \n",
            "\n",
            "\n",
            "[MoviePy] Building file /content/gdrive/My Drive/AI/videoedit/gif1.gif with imageio\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|██████████| 39/39 [00:02<00:00, 15.16it/s]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#from moviepy.editor import VideoFileClip\n",
        "#videoClip = VideoFileClip(\"my-life.mp4\")\n",
        "videoClip.write_gif(\"my-life.gif\")"
      ],
      "metadata": {
        "id": "gYjm17URaSGg"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#second new approach\n",
        "import moviepy.editor as mp\n",
        "\n",
        "video = mp.VideoFileClip(videopath)\n",
        "\n",
        "# delete video fragment from 00:30 to 01:00\n",
        "#segments = [tuple(words_timestamp[5]), (words_timestamp[0][0], words_timestamp[1][1])]\n",
        "#segments = [(4, 5),\n",
        "#            (2, 3)]\n",
        "\n",
        "\n",
        "clips = []  # list of all video fragments\n",
        "for start_seconds, end_seconds in segments:\n",
        "    # crop a video clip and add it to list\n",
        "    c = video.subclip(start_seconds, end_seconds)\n",
        "    clips.append(c)\n",
        "\n",
        "final_clip = mp.concatenate_videoclips(clips)\n",
        "final_clip.write_videofile(\"/content/gdrive/My Drive/AI/videoedit/test2.mp4\")\n",
        "final_clip.close()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "iZCgBysZ_CHR",
        "outputId": "75c59e9d-c95a-4b74-ec05-499b70b05f4e"
      },
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[MoviePy] >>>> Building video /content/gdrive/My Drive/AI/videoedit/test2.mp4\n",
            "[MoviePy] Writing audio in test2TEMP_MPY_wvf_snd.mp3\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|██████████| 18/18 [00:00<00:00, 240.96it/s]"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[MoviePy] Done.\n",
            "[MoviePy] Writing video /content/gdrive/My Drive/AI/videoedit/test2.mp4\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\n",
            "100%|██████████| 20/20 [00:00<00:00, 119.78it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[MoviePy] Done.\n",
            "[MoviePy] >>>> Video ready: /content/gdrive/My Drive/AI/videoedit/test2.mp4 \n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "CQ_0_xa1wKX-"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "vXlYbC8HVM7Y"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "7bZTgkKrA5hj"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "jCcPhacE_4ef"
      },
      "outputs": [],
      "source": [
        "def cut_timestamps_to_video(video_in, transcription, text_in, timestamps):\n",
        "    \"\"\"\n",
        "    Given original video input, text transcript + timestamps,\n",
        "    and edit ext cuts video segments into a single video\n",
        "    \"\"\"\n",
        "    global total_cuts_since_reboot\n",
        "\n",
        "    video_path = Path(video_in)\n",
        "    video_file_name = video_path.stem\n",
        "    if(video_in == None or text_in == None or transcription == None):\n",
        "        raise ValueError(\"Inputs undefined\")\n",
        "\n",
        "    d = Differ()\n",
        "    # compare original transcription with edit text\n",
        "    diff_chars = d.compare(transcription, text_in)\n",
        "    # remove all text aditions from diff\n",
        "    filtered = list(filter(lambda x: x[0] != '+', diff_chars))\n",
        "\n",
        "    # filter timestamps to be removed\n",
        "    # timestamps_to_cut = [b for (a,b) in zip(filtered, timestamps_var) if a[0]== '-' ]\n",
        "    # return diff tokes and cutted video!!\n",
        "\n",
        "    # groupping character timestamps so there are less cuts\n",
        "    idx = 0\n",
        "    grouped = {}\n",
        "    for(a, b) in zip(filtered, timestamps):\n",
        "        if a[0] != '-':\n",
        "            if idx in grouped:\n",
        "                grouped[idx].append(b)\n",
        "            else:\n",
        "                grouped[idx] = []\n",
        "                grouped[idx].append(b)\n",
        "        else:\n",
        "            idx += 1\n",
        "\n",
        "    # after grouping, gets the lower and upter start and time for each group\n",
        "    timestamps_to_cut = [[v[0][1], v[-1][2]] for v in grouped.values()]\n",
        "\n",
        "    between_str = '+'.join(\n",
        "        map(lambda t: f'between(t,{t[0]},{t[1]})', timestamps_to_cut))\n",
        "\n",
        "    if timestamps_to_cut:\n",
        "        video_file = ffmpeg.input(video_in)\n",
        "        video = video_file.video.filter(\"select\", f'({between_str})').filter(\"setpts\", \"N/FRAME_RATE/TB\")\n",
        "        audio = video_file.audio.filter(\"aselect\", f'({between_str})').filter(\"asetpts\", \"N/SR/TB\")\n",
        "\n",
        "        output_video = f'./videos_out/{video_file_name}.mp4'\n",
        "        ffmpeg.concat(video, audio, v=1, a=1).output(\n",
        "            output_video).overwrite_output().global_args('-loglevel', 'quiet').run()\n",
        "    else:\n",
        "        output_video = video_in\n",
        "\n",
        "    tokens = [(token[2:], token[0] if token[0] != \" \" else None)\n",
        "              for token in filtered]\n",
        "\n",
        "    total_cuts_since_reboot += 1\n",
        "    print(\"\\n\\ntotal_cuts_since_reboot: \", total_cuts_since_reboot, \"\\n\\n\")\n",
        "    return (tokens, output_video)\n",
        "\n",
        "\n",
        "# ---- Gradio Layout -----\n",
        "video_in = gr.Video(label=\"Video file\")\n",
        "text_in = gr.Textbox(label=\"Transcription\", lines=10, interactive=True)\n",
        "video_out = gr.Video(label=\"Video Out\")\n",
        "diff_out = gr.HighlightedText(label=\"Cuts Diffs\", combine_adjacent=True)\n",
        "examples = gr.components.Dataset(\n",
        "    components=[video_in], samples=VIDEOS, type=\"index\")\n",
        "\n",
        "demo = gr.Blocks(enable_queue=True, css='''\n",
        "#cut_btn, #reset_btn { align-self:stretch; }\n",
        "#\\\\31 3 { max-width: 540px; }\n",
        ".output-markdown {max-width: 65ch !important;}\n",
        "''')\n",
        "demo.encrypt = False\n",
        "with demo:\n",
        "    transcription_var = gr.Variable()\n",
        "    timestamps_var = gr.Variable()\n",
        "    with gr.Row():\n",
        "        with gr.Column():\n",
        "            gr.Markdown('''\n",
        "            # Edit Video By Editing Text\n",
        "            This project is a quick proof of concept of a simple video editor where the edits\n",
        "            are made by editing the audio transcription.\n",
        "            Using the [Huggingface Automatic Speech Recognition Pipeline](https://huggingface.co/tasks/automatic-speech-recognition)\n",
        "            with a fine tuned [Wav2Vec2 model using Connectionist Temporal Classification (CTC)](https://huggingface.co/facebook/wav2vec2-large-960h-lv60-self)\n",
        "            you can predict not only the text transcription but also the [character or word base timestamps](https://huggingface.co/docs/transformers/v4.19.2/en/main_classes/pipelines#transformers.AutomaticSpeechRecognitionPipeline.__call__.return_timestamps)\n",
        "            ''')\n",
        "\n",
        "    with gr.Row():\n",
        "\n",
        "        examples.render()\n",
        "\n",
        "        def load_example(id):\n",
        "            video = SAMPLES[id]['video']\n",
        "            transcription = SAMPLES[id]['transcription'].lower()\n",
        "            timestamps = SAMPLES[id]['timestamps']\n",
        "\n",
        "            return (video, transcription, transcription, timestamps)\n",
        "\n",
        "        examples.click(\n",
        "            load_example,\n",
        "            inputs=[examples],\n",
        "            outputs=[video_in, text_in, transcription_var, timestamps_var],\n",
        "            queue=False)\n",
        "    with gr.Row():\n",
        "        with gr.Column():\n",
        "            video_in.render()\n",
        "            transcribe_btn = gr.Button(\"Transcribe Audio\")\n",
        "            transcribe_btn.click(speech_to_text, [video_in], [\n",
        "                text_in, transcription_var, timestamps_var])\n",
        "\n",
        "    with gr.Row():\n",
        "        gr.Markdown('''\n",
        "        ### Now edit as text\n",
        "        After running the video transcription, you can make cuts to the text below (only cuts, not additions!)''')\n",
        "\n",
        "    with gr.Row():\n",
        "        with gr.Column():\n",
        "            text_in.render()\n",
        "            with gr.Row():\n",
        "                cut_btn = gr.Button(\"Cut to video\", elem_id=\"cut_btn\")\n",
        "                # send audio path and hidden variables\n",
        "                cut_btn.click(cut_timestamps_to_video, [\n",
        "                    video_in, transcription_var, text_in, timestamps_var], [diff_out, video_out])\n",
        "\n",
        "                reset_transcription = gr.Button(\n",
        "                    \"Reset to last trascription\", elem_id=\"reset_btn\")\n",
        "                reset_transcription.click(\n",
        "                    lambda x: x, transcription_var, text_in)\n",
        "        with gr.Column():\n",
        "            video_out.render()\n",
        "            diff_out.render()\n",
        "    with gr.Row():\n",
        "        gr.Markdown('''\n",
        "        #### Video Credits\n",
        "        1. [Cooking](https://vimeo.com/573792389)\n",
        "        1. [Shia LaBeouf \"Just Do It\"](https://www.youtube.com/watch?v=n2lTxIk_Dr0)\n",
        "        1. [Mark Zuckerberg & Yuval Noah Harari in Conversation](https://www.youtube.com/watch?v=Boj9eD0Wug8)\n",
        "        ''')\n",
        "\n",
        "if __name__ == \"__main__\":\n",
        "    demo.launch(debug=True)"
      ]
    }
  ]
}