{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Image Caption Generator"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from matplotlib import pyplot as plt\n",
    "import pandas as pd\n",
    "import re\n",
    "import cv2\n",
    "\n",
    "import os\n",
    "from tqdm import tqdm"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Dataset Loading"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "PATH = 'Dataset/'\n",
    "\n",
    "IMAGE_PATH = PATH + 'images/'\n",
    "LABEL_PATH = PATH + 'captions.csv'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Read LABEL_PATH using pandas\n",
    "df = pd.read_csv(LABEL_PATH, delimiter=',')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>image</th>\n",
       "      <th>caption</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1000268201_693b08cb0e.jpg</td>\n",
       "      <td>A child in a pink dress is climbing up a set o...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1000268201_693b08cb0e.jpg</td>\n",
       "      <td>A girl going into a wooden building .</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1000268201_693b08cb0e.jpg</td>\n",
       "      <td>A little girl climbing into a wooden playhouse .</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1000268201_693b08cb0e.jpg</td>\n",
       "      <td>A little girl climbing the stairs to her playh...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1000268201_693b08cb0e.jpg</td>\n",
       "      <td>A little girl in a pink dress going into a woo...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       image  \\\n",
       "0  1000268201_693b08cb0e.jpg   \n",
       "1  1000268201_693b08cb0e.jpg   \n",
       "2  1000268201_693b08cb0e.jpg   \n",
       "3  1000268201_693b08cb0e.jpg   \n",
       "4  1000268201_693b08cb0e.jpg   \n",
       "\n",
       "                                             caption  \n",
       "0  A child in a pink dress is climbing up a set o...  \n",
       "1              A girl going into a wooden building .  \n",
       "2   A little girl climbing into a wooden playhouse .  \n",
       "3  A little girl climbing the stairs to her playh...  \n",
       "4  A little girl in a pink dress going into a woo...  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot image and caption from the dataframe\n",
    "def plot_image_caption(df, idx):\n",
    "    img = plt.imread(IMAGE_PATH + df.iloc[idx]['image'])\n",
    "    plt.imshow(img)\n",
    "    plt.title(df.iloc[idx]['caption'])\n",
    "    plt.axis('off')\n",
    "    plt.show()\n",
    "\n",
    "plot_image_caption(df, 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "Images = []\n",
    "Captions = []"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "Captions = df['caption'].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "captions = []\n",
    "for i in Captions:\n",
    "    i = i.lower()\n",
    "    # Clean captions and remove puncuations usng regex\n",
    "    i = re.sub(r'[^\\w\\s]', '', i)\n",
    "    captions.append(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'a child in a pink dress is climbing up a set of stairs in an entry way '"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "captions[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Word Embedding"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# add start and end to captions\n",
    "\n",
    "newCaps = []\n",
    "maxLen = 0\n",
    "wordList = ['','START','END']\n",
    "for caption in captions :\n",
    "    cap = ['START']\n",
    "    captionWords = caption.strip().split(' ')\n",
    "    cap.extend(captionWords)\n",
    "    for i in captionWords :\n",
    "        if i not in wordList :\n",
    "            wordList.append(i)\n",
    "    cap.append('END')\n",
    "    if len(cap) > maxLen :\n",
    "        maxLen = len(cap)\n",
    "    newCaps.append(cap)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "39"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "maxLen"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8831"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(wordList)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['',\n",
       " 'START',\n",
       " 'END',\n",
       " 'a',\n",
       " 'child',\n",
       " 'in',\n",
       " 'pink',\n",
       " 'dress',\n",
       " 'is',\n",
       " 'climbing',\n",
       " 'up',\n",
       " 'set',\n",
       " 'of',\n",
       " 'stairs',\n",
       " 'an',\n",
       " 'entry',\n",
       " 'way',\n",
       " 'girl',\n",
       " 'going',\n",
       " 'into',\n",
       " 'wooden',\n",
       " 'building',\n",
       " 'little',\n",
       " 'playhouse',\n",
       " 'the',\n",
       " 'to',\n",
       " 'her',\n",
       " 'cabin',\n",
       " 'black',\n",
       " 'dog',\n",
       " 'and',\n",
       " 'spotted',\n",
       " 'are',\n",
       " 'fighting',\n",
       " 'tricolored',\n",
       " 'playing',\n",
       " 'with',\n",
       " 'each',\n",
       " 'other',\n",
       " 'on',\n",
       " 'road',\n",
       " 'white',\n",
       " 'brown',\n",
       " 'spots',\n",
       " 'staring',\n",
       " 'at',\n",
       " 'street',\n",
       " 'two',\n",
       " 'dogs',\n",
       " 'different',\n",
       " 'breeds',\n",
       " 'looking',\n",
       " 'pavement',\n",
       " 'moving',\n",
       " 'toward',\n",
       " 'covered',\n",
       " 'paint',\n",
       " 'sits',\n",
       " 'front',\n",
       " 'painted',\n",
       " 'rainbow',\n",
       " 'hands',\n",
       " 'bowl',\n",
       " 'sitting',\n",
       " 'large',\n",
       " 'small',\n",
       " 'grass',\n",
       " 'plays',\n",
       " 'fingerpaints',\n",
       " 'canvas',\n",
       " 'it',\n",
       " 'there',\n",
       " 'pigtails',\n",
       " 'painting',\n",
       " 'young',\n",
       " 'outside',\n",
       " 'man',\n",
       " 'lays',\n",
       " 'bench',\n",
       " 'while',\n",
       " 'his',\n",
       " 'by',\n",
       " 'him',\n",
       " 'which',\n",
       " 'also',\n",
       " 'tied',\n",
       " 'sleeping',\n",
       " 'next',\n",
       " 'shirtless',\n",
       " 'lies',\n",
       " 'park',\n",
       " 'laying',\n",
       " 'holding',\n",
       " 'leash',\n",
       " 'ground',\n",
       " 'orange',\n",
       " 'hat',\n",
       " 'starring',\n",
       " 'something',\n",
       " 'wears',\n",
       " 'glasses',\n",
       " 'gauges',\n",
       " 'wearing',\n",
       " 'blitz',\n",
       " 'beer',\n",
       " 'can',\n",
       " 'crocheted',\n",
       " 'pierced',\n",
       " 'ears',\n",
       " 'rope',\n",
       " 'net',\n",
       " 'red',\n",
       " 'roping',\n",
       " 'climbs',\n",
       " 'bridge',\n",
       " 'grips',\n",
       " 'onto',\n",
       " 'ropes',\n",
       " 'playground',\n",
       " 'running',\n",
       " 'grassy',\n",
       " 'garden',\n",
       " 'surrounded',\n",
       " 'fence',\n",
       " 'through',\n",
       " 'boston',\n",
       " 'terrier',\n",
       " 'lush',\n",
       " 'green',\n",
       " 'runs',\n",
       " 'near',\n",
       " 'shakes',\n",
       " 'its',\n",
       " 'head',\n",
       " 'shore',\n",
       " 'ball',\n",
       " 'edge',\n",
       " 'beach',\n",
       " 'feet',\n",
       " 'stands',\n",
       " 'shaking',\n",
       " 'off',\n",
       " 'water',\n",
       " 'standing',\n",
       " 'turned',\n",
       " 'one',\n",
       " 'side',\n",
       " 'boy',\n",
       " 'smiles',\n",
       " 'stony',\n",
       " 'wall',\n",
       " 'city',\n",
       " 'overalls',\n",
       " 'working',\n",
       " 'stone',\n",
       " 'aross',\n",
       " 'walking',\n",
       " 'paved',\n",
       " 'metal',\n",
       " 'pole',\n",
       " 'behind',\n",
       " 'smiling',\n",
       " 'shirt',\n",
       " 'blue',\n",
       " 'jeans',\n",
       " 'rock',\n",
       " 'leaps',\n",
       " 'over',\n",
       " 'log',\n",
       " 'grey',\n",
       " 'leaping',\n",
       " 'fallen',\n",
       " 'tree',\n",
       " 'mottled',\n",
       " 'collar',\n",
       " 'jumping',\n",
       " 'jumped',\n",
       " 'stump',\n",
       " 'snow',\n",
       " 'field',\n",
       " 'surface',\n",
       " 'displaying',\n",
       " 'pictures',\n",
       " 'skier',\n",
       " 'skis',\n",
       " 'past',\n",
       " 'another',\n",
       " 'paintings',\n",
       " 'person',\n",
       " 'framed',\n",
       " 'looks',\n",
       " 'trees',\n",
       " 'artwork',\n",
       " 'for',\n",
       " 'sale',\n",
       " 'collage',\n",
       " 'cliff',\n",
       " 'group',\n",
       " 'people',\n",
       " 'belays',\n",
       " 'seven',\n",
       " 'climbers',\n",
       " 'ascending',\n",
       " 'face',\n",
       " 'whilst',\n",
       " 'several',\n",
       " 'row',\n",
       " 'watches',\n",
       " 'holds',\n",
       " 'line',\n",
       " 'chases',\n",
       " 'from',\n",
       " 'sprinkler',\n",
       " 'lawn',\n",
       " 'hose',\n",
       " 'away',\n",
       " 'prepares',\n",
       " 'catch',\n",
       " 'thrown',\n",
       " 'object',\n",
       " 'nearby',\n",
       " 'cars',\n",
       " 'about',\n",
       " 'yellow',\n",
       " 'mouth',\n",
       " 'toy',\n",
       " 'ready',\n",
       " 'flying',\n",
       " 'air',\n",
       " 'after',\n",
       " 'get',\n",
       " 'jumps',\n",
       " 'towards',\n",
       " 'trying',\n",
       " 'midair',\n",
       " 'woman',\n",
       " 'waters',\n",
       " 'big',\n",
       " 'lake',\n",
       " 'lone',\n",
       " 'duck',\n",
       " 'swimming',\n",
       " 'around',\n",
       " 'watching',\n",
       " 'waves',\n",
       " 'hand',\n",
       " 'facing',\n",
       " 'skyline',\n",
       " 'couple',\n",
       " 'infant',\n",
       " 'being',\n",
       " 'held',\n",
       " 'male',\n",
       " 'pond',\n",
       " 'stroller',\n",
       " 'sit',\n",
       " 'baby',\n",
       " 'their',\n",
       " 'newborn',\n",
       " 'under',\n",
       " 'care',\n",
       " 'along',\n",
       " 'body',\n",
       " 'outdoors',\n",
       " 'surf',\n",
       " 'lab',\n",
       " 'tags',\n",
       " 'frolicks',\n",
       " 'splashes',\n",
       " 'this',\n",
       " 'splashing',\n",
       " 'drilling',\n",
       " 'hole',\n",
       " 'ice',\n",
       " 'frozen',\n",
       " 'men',\n",
       " 'fishing',\n",
       " 'play',\n",
       " 'making',\n",
       " 'turn',\n",
       " 'soft',\n",
       " 'sand',\n",
       " 'together',\n",
       " 'tan',\n",
       " 'sandy',\n",
       " 'uses',\n",
       " 'picks',\n",
       " 'crampons',\n",
       " 'scale',\n",
       " 'climber',\n",
       " 'jacket',\n",
       " 'pants',\n",
       " 'scaling',\n",
       " 'waterfall',\n",
       " 'carries',\n",
       " 'as',\n",
       " 'he',\n",
       " 'walks',\n",
       " 'carrying',\n",
       " 'has',\n",
       " 'item',\n",
       " 'wet',\n",
       " 'kayak',\n",
       " 'life',\n",
       " 'jackets',\n",
       " 'rowing',\n",
       " 'canoe',\n",
       " 'gentle',\n",
       " 'ride',\n",
       " 'courtyard',\n",
       " 'catching',\n",
       " 'snaps',\n",
       " 'lunges',\n",
       " 'chocolate',\n",
       " 'too',\n",
       " 'late',\n",
       " 'captures',\n",
       " 'driveway',\n",
       " 'stick',\n",
       " 'kneeling',\n",
       " 'goalie',\n",
       " 'hockey',\n",
       " 'guarding',\n",
       " 'goal',\n",
       " 'kid',\n",
       " 'rink',\n",
       " 'right',\n",
       " 'crouches',\n",
       " 'modern',\n",
       " 'art',\n",
       " 'structure',\n",
       " 'glass',\n",
       " 'reads',\n",
       " 'newspaper',\n",
       " 'sculpture',\n",
       " 'office',\n",
       " 'statue',\n",
       " 'backpack',\n",
       " 'buildings',\n",
       " 'reading',\n",
       " 'tent',\n",
       " 'enter',\n",
       " 'setting',\n",
       " 'hut',\n",
       " 'iced',\n",
       " 'tarp',\n",
       " 'snowy',\n",
       " 'three',\n",
       " 'hill',\n",
       " 'sky',\n",
       " 'them',\n",
       " 'stand',\n",
       " 'kneels',\n",
       " 'skyscraper',\n",
       " 'very',\n",
       " 'tall',\n",
       " 'distance',\n",
       " 'camera',\n",
       " 'bites',\n",
       " 'hard',\n",
       " 'treat',\n",
       " 'biting',\n",
       " 'baked',\n",
       " 'good',\n",
       " 'putting',\n",
       " 'both',\n",
       " 'eats',\n",
       " 'food',\n",
       " 'table',\n",
       " 'eating',\n",
       " 'pizza',\n",
       " 'tin',\n",
       " 'dish',\n",
       " 'mountainside',\n",
       " 'check',\n",
       " 'out',\n",
       " 'view',\n",
       " 'hilltop',\n",
       " 'overlooking',\n",
       " 'valley',\n",
       " 'hang',\n",
       " 'top',\n",
       " 'overlook',\n",
       " 'rest',\n",
       " 'ledge',\n",
       " 'above',\n",
       " 'moutains',\n",
       " 'down',\n",
       " 'many',\n",
       " 'inflatable',\n",
       " 'boats',\n",
       " 'kayakers',\n",
       " 'railing',\n",
       " 'rafts',\n",
       " 'below',\n",
       " 'crowd',\n",
       " 'jersey',\n",
       " 'pose',\n",
       " 'some',\n",
       " 'multiracial',\n",
       " 'posing',\n",
       " 'picture',\n",
       " 'asian',\n",
       " 'blond',\n",
       " 'background',\n",
       " 'guy',\n",
       " 'striped',\n",
       " 'takeout',\n",
       " 'television',\n",
       " 'floor',\n",
       " 'fast',\n",
       " 'meal',\n",
       " 'someone',\n",
       " 'tv',\n",
       " 'teens',\n",
       " 'rail',\n",
       " 'crowded',\n",
       " 'takes',\n",
       " 'jump',\n",
       " 'skateboard',\n",
       " 'performing',\n",
       " 'trick',\n",
       " 'leans',\n",
       " 'skateboarder',\n",
       " 'doing',\n",
       " 'board',\n",
       " 'platform',\n",
       " 'skateboarders',\n",
       " 'paddling',\n",
       " 'river',\n",
       " 'seen',\n",
       " 'kayaking',\n",
       " 'paddles',\n",
       " 'boat',\n",
       " 'paddle',\n",
       " 'shallow',\n",
       " 'girls',\n",
       " 'ocean',\n",
       " 'four',\n",
       " 'children',\n",
       " 'pajamas',\n",
       " 'have',\n",
       " 'pillow',\n",
       " 'fight',\n",
       " 'kids',\n",
       " 'pillowfight',\n",
       " 'bed',\n",
       " 'having',\n",
       " 'constructions',\n",
       " 'workers',\n",
       " 'beam',\n",
       " 'taking',\n",
       " 'break',\n",
       " 'construction',\n",
       " 'ibeam',\n",
       " 'take',\n",
       " 'seat',\n",
       " 'steel',\n",
       " 'boys',\n",
       " 'puddle',\n",
       " 'balloon',\n",
       " 'mud',\n",
       " 'sunny',\n",
       " 'day',\n",
       " 'appears',\n",
       " 'wait',\n",
       " 'hailing',\n",
       " 'taxi',\n",
       " 'signaling',\n",
       " 'traffic',\n",
       " 'blonde',\n",
       " 'hair',\n",
       " 'tube',\n",
       " 'waving',\n",
       " 'arm',\n",
       " 'oncoming',\n",
       " 'brochure',\n",
       " 'train',\n",
       " 'rides',\n",
       " 'magizine',\n",
       " 'book',\n",
       " 'pamphlet',\n",
       " 'rocky',\n",
       " 'run',\n",
       " 'across',\n",
       " 'stones',\n",
       " 'area',\n",
       " 'descends',\n",
       " 'end',\n",
       " 'high',\n",
       " 'diving',\n",
       " 'pool',\n",
       " 'dive',\n",
       " 'window',\n",
       " 'overshirt',\n",
       " 'tank',\n",
       " 'chrome',\n",
       " 'door',\n",
       " 'puts',\n",
       " 'elevator',\n",
       " 'lightcolored',\n",
       " 'light',\n",
       " 'swim',\n",
       " 'shorts',\n",
       " 'trunks',\n",
       " 'arms',\n",
       " 'outstretched',\n",
       " 'hiker',\n",
       " 'bluff',\n",
       " 'mountains',\n",
       " 'ski',\n",
       " 's',\n",
       " 'landscape',\n",
       " 'snowcovered',\n",
       " 'mountain',\n",
       " 'beautiful',\n",
       " 'pauses',\n",
       " 'mountaintop',\n",
       " 'attempting',\n",
       " 'purple',\n",
       " 'low',\n",
       " 'cut',\n",
       " 'yard',\n",
       " 'frisbee',\n",
       " 'parking',\n",
       " 'lot',\n",
       " 'middle',\n",
       " 'during',\n",
       " 'heavy',\n",
       " 'mat',\n",
       " 'between',\n",
       " 'suv',\n",
       " 'pickup',\n",
       " 'open',\n",
       " 'busy',\n",
       " 'terrain',\n",
       " 'woolly',\n",
       " 'doberman',\n",
       " 'chasing',\n",
       " 'catches',\n",
       " 'tennis',\n",
       " 'multicolor',\n",
       " 'balloons',\n",
       " 'night',\n",
       " 'hot',\n",
       " 'lit',\n",
       " 'lined',\n",
       " 'nighttime',\n",
       " 'helmet',\n",
       " 'bike',\n",
       " 'miniature',\n",
       " 'dirt',\n",
       " 'bicycle',\n",
       " 'race',\n",
       " 'pedals',\n",
       " 'quickly',\n",
       " 'bmx',\n",
       " 'eight',\n",
       " 'gathered',\n",
       " 'dark',\n",
       " 'porch',\n",
       " 'darkened',\n",
       " 'room',\n",
       " 'throwing',\n",
       " 'cleans',\n",
       " 'bubbles',\n",
       " 'suds',\n",
       " 'wiped',\n",
       " 'clean',\n",
       " 'foam',\n",
       " 'ramp',\n",
       " 'soapy',\n",
       " 'getting',\n",
       " 'cleaned',\n",
       " 'slides',\n",
       " 'slide',\n",
       " 'wading',\n",
       " 'toys',\n",
       " 'floating',\n",
       " 'backyard',\n",
       " 'sliding',\n",
       " 'colorful',\n",
       " 'tubes',\n",
       " 'falling',\n",
       " 'colored',\n",
       " 'wetsuit',\n",
       " 'toddler',\n",
       " 'waiting',\n",
       " 'come',\n",
       " 'so',\n",
       " 'droplets',\n",
       " 'fly',\n",
       " 'throws',\n",
       " 'sticks',\n",
       " 'tongue',\n",
       " 'make',\n",
       " 'faces',\n",
       " 'sticking',\n",
       " 'look',\n",
       " 'silly',\n",
       " 'horse',\n",
       " 'sweatshirt',\n",
       " 'fire',\n",
       " 'barrel',\n",
       " 'lead',\n",
       " 'horses',\n",
       " 'contained',\n",
       " 'bulldog',\n",
       " 'sheep',\n",
       " 'boxer',\n",
       " 'pushing',\n",
       " 'anouther',\n",
       " 'skinny',\n",
       " 'smaller',\n",
       " 'int',\n",
       " 'various',\n",
       " 'sizes',\n",
       " 'lady',\n",
       " 'no',\n",
       " 'dock',\n",
       " 'deck',\n",
       " 'closeup',\n",
       " 'that',\n",
       " 'paws',\n",
       " 'lying',\n",
       " 'resting',\n",
       " 'tiled',\n",
       " 'eyes',\n",
       " 'rests',\n",
       " 'patio',\n",
       " 'bricks',\n",
       " 'artificial',\n",
       " 'safety',\n",
       " 'harness',\n",
       " 'indoor',\n",
       " 'rocks',\n",
       " 'ring',\n",
       " 'jumphouse',\n",
       " 'teenage',\n",
       " 'seating',\n",
       " 'inflated',\n",
       " 'family',\n",
       " 'tractor',\n",
       " 'polaris',\n",
       " 'vehicle',\n",
       " 'played',\n",
       " 'wheeler',\n",
       " 'riding',\n",
       " 'atv',\n",
       " 'costume',\n",
       " 'left',\n",
       " 'sequined',\n",
       " 'feather',\n",
       " 'sidewalk',\n",
       " 'salmon',\n",
       " 'bikini',\n",
       " 'outfit',\n",
       " 'drinking',\n",
       " 'pop',\n",
       " 'approached',\n",
       " 'flamboyant',\n",
       " 'dressed',\n",
       " 'feathered',\n",
       " 'headress',\n",
       " 'skiiers',\n",
       " 'forest',\n",
       " 'skiing',\n",
       " 'wooded',\n",
       " 'crosscountry',\n",
       " 'skiers',\n",
       " 'woodland',\n",
       " 'trail',\n",
       " 'woods',\n",
       " 'hikers',\n",
       " 'pathway',\n",
       " 'path',\n",
       " 'happily',\n",
       " 'energetic',\n",
       " 'mother',\n",
       " 'boardwalk',\n",
       " 'sea',\n",
       " 'pier',\n",
       " 'evening',\n",
       " 'pony',\n",
       " 'wintertime',\n",
       " 'atop',\n",
       " 'draft',\n",
       " 'n',\n",
       " 'daft',\n",
       " 'pull',\n",
       " 'cart',\n",
       " 'golden',\n",
       " 'sleigh',\n",
       " 'driven',\n",
       " 'coat',\n",
       " 'pulling',\n",
       " 'carriage',\n",
       " 'sled',\n",
       " 'steered',\n",
       " 'sheer',\n",
       " 'using',\n",
       " 'flat',\n",
       " 'rappels',\n",
       " 'steep',\n",
       " 'incline',\n",
       " 'vest',\n",
       " 'inside',\n",
       " 'dome',\n",
       " 'shaft',\n",
       " 'cave',\n",
       " 'shows',\n",
       " 'spelunkers',\n",
       " 'cavern',\n",
       " 'bathed',\n",
       " 'sunlight',\n",
       " 'backpackers',\n",
       " 'lay',\n",
       " 'dry',\n",
       " 'camp',\n",
       " 'gear',\n",
       " 'chalk',\n",
       " 'portrait',\n",
       " 'stream',\n",
       " 'drawing',\n",
       " 'barnlike',\n",
       " 'elaborate',\n",
       " 'illustration',\n",
       " 'deep',\n",
       " 'pile',\n",
       " 'fountain',\n",
       " 'fountains',\n",
       " 'sprayed',\n",
       " 'corgi',\n",
       " 'tunnel',\n",
       " 'course',\n",
       " 'obstacle',\n",
       " 'obedience',\n",
       " 'swimsuit',\n",
       " 'handrail',\n",
       " 'bathing',\n",
       " 'suit',\n",
       " 'spray',\n",
       " 'soaked',\n",
       " 'jet',\n",
       " 'shower',\n",
       " 'gets',\n",
       " 'underwater',\n",
       " 'redheaded',\n",
       " 'swims',\n",
       " 'gun',\n",
       " 'foot',\n",
       " 'aims',\n",
       " 'fireplace',\n",
       " 'new',\n",
       " 'lightup',\n",
       " 'pointed',\n",
       " 'alone',\n",
       " 'jagged',\n",
       " 'snowmobile',\n",
       " 'mid',\n",
       " 'snowmobiler',\n",
       " 'flies',\n",
       " 'rider',\n",
       " 'or',\n",
       " 'machine',\n",
       " 'pine',\n",
       " 'rural',\n",
       " 'snowmobiles',\n",
       " 'helmets',\n",
       " 'goggles',\n",
       " 'snowmobiling',\n",
       " 'helmeted',\n",
       " 'drive',\n",
       " 'atvs',\n",
       " 'heads',\n",
       " 'wheel',\n",
       " 'wheelers',\n",
       " 'empty',\n",
       " 'all',\n",
       " 'gin',\n",
       " 'fourwheeler',\n",
       " 'airborne',\n",
       " 'quad',\n",
       " 'harvested',\n",
       " 'cornfield',\n",
       " 'happy',\n",
       " 'od',\n",
       " 'playfully',\n",
       " 'soccer',\n",
       " 'tucked',\n",
       " 'tshirt',\n",
       " 'artist',\n",
       " 'paints',\n",
       " 'clouds',\n",
       " 'braids',\n",
       " 'colors',\n",
       " 'paper',\n",
       " 'cyclist',\n",
       " 'curved',\n",
       " 'aerodynamic',\n",
       " 'sharp',\n",
       " 'curve',\n",
       " 'pedaling',\n",
       " 'cows',\n",
       " 'graze',\n",
       " 'biker',\n",
       " 'fetch',\n",
       " 'pounces',\n",
       " 'cine',\n",
       " 'old',\n",
       " 'fashioned',\n",
       " 'video',\n",
       " 'steadies',\n",
       " 'aim',\n",
       " 'rosy',\n",
       " 'cheeks',\n",
       " 'lips',\n",
       " 'border',\n",
       " 'collie',\n",
       " 'audience',\n",
       " 'dug',\n",
       " 'watch',\n",
       " 'agile',\n",
       " 'onlookers',\n",
       " 'closely',\n",
       " 'smooth',\n",
       " 'stacking',\n",
       " 'against',\n",
       " 'backdrop',\n",
       " 'shoes',\n",
       " 'rappeling',\n",
       " 'headlamp',\n",
       " 'attached',\n",
       " 'snakeskin',\n",
       " 'sprays',\n",
       " 'frog',\n",
       " 'public',\n",
       " 'wood',\n",
       " 'barrior',\n",
       " 'animal',\n",
       " 'bird',\n",
       " 'seeds',\n",
       " 'sunflower',\n",
       " 'clinging',\n",
       " 'finger',\n",
       " 'wades',\n",
       " 'guided',\n",
       " 'laughs',\n",
       " 'playful',\n",
       " 'beige',\n",
       " 'torwards',\n",
       " 'outdoor',\n",
       " 'handstand',\n",
       " 'does',\n",
       " 'sheets',\n",
       " 'upside',\n",
       " 'snowboard',\n",
       " 'surfboard',\n",
       " 'bikes',\n",
       " 'traveling',\n",
       " 'worn',\n",
       " 'motorcycles',\n",
       " 'motorbikes',\n",
       " 'follow',\n",
       " 'dirtbikes',\n",
       " 'offroad',\n",
       " 'garment',\n",
       " 'flag',\n",
       " 'crescent',\n",
       " 'moon',\n",
       " 'star',\n",
       " 'gown',\n",
       " 'muslim',\n",
       " 'helps',\n",
       " 'wave',\n",
       " 'half',\n",
       " 'naked',\n",
       " 'chair',\n",
       " 'older',\n",
       " 'back',\n",
       " 'relaxes',\n",
       " 'adobe',\n",
       " 'where',\n",
       " 'bicycles',\n",
       " 'propped',\n",
       " 'cap',\n",
       " 'close',\n",
       " 'parked',\n",
       " 'relaxing',\n",
       " 'folding',\n",
       " 'topless',\n",
       " 'slippers',\n",
       " 'navy',\n",
       " 'reclining',\n",
       " 'hauling',\n",
       " 'retrieve',\n",
       " 'mouths',\n",
       " 'tug',\n",
       " 'chew',\n",
       " 'haired',\n",
       " 'bottled',\n",
       " 'drink',\n",
       " 'tilted',\n",
       " 'spiked',\n",
       " 'party',\n",
       " 'streets',\n",
       " 'they',\n",
       " 'women',\n",
       " 'parade',\n",
       " 'neckdeep',\n",
       " 'vegetation',\n",
       " 'filled',\n",
       " 'bushes',\n",
       " 'creating',\n",
       " 'splash',\n",
       " 'seaweed',\n",
       " 'lav',\n",
       " 'swimmers',\n",
       " 'kelp',\n",
       " 'foreground',\n",
       " 'sandals',\n",
       " 'short',\n",
       " 'sleeved',\n",
       " 'pinstripe',\n",
       " 'snows',\n",
       " 'furry',\n",
       " 'attempts',\n",
       " 'itself',\n",
       " 'self',\n",
       " 'backpacks',\n",
       " 'placed',\n",
       " 'cardboard',\n",
       " 'bus',\n",
       " 'station',\n",
       " 'bouncing',\n",
       " 'folded',\n",
       " 'beds',\n",
       " 'bedroom',\n",
       " 'snowboarder',\n",
       " 'slope',\n",
       " 'boarders',\n",
       " 'snowboarders',\n",
       " 'slopes',\n",
       " 'clothing',\n",
       " 'store',\n",
       " 'opening',\n",
       " 'stores',\n",
       " 'piece',\n",
       " 'attire',\n",
       " 'car',\n",
       " 'strip',\n",
       " 'boots',\n",
       " 'stepping',\n",
       " 'van',\n",
       " 'wear',\n",
       " 'game',\n",
       " 'plants',\n",
       " 'crossing',\n",
       " 'greenery',\n",
       " 'suspension',\n",
       " 'tropical',\n",
       " 'caution',\n",
       " 'sign',\n",
       " 'beside',\n",
       " 'bright',\n",
       " 'truck',\n",
       " 'others',\n",
       " 'helping',\n",
       " 'step',\n",
       " 'pulled',\n",
       " 'passengers',\n",
       " 'load',\n",
       " 'brightly',\n",
       " 'poses',\n",
       " 'pig',\n",
       " 'hugs',\n",
       " 'who',\n",
       " 'embracing',\n",
       " 'event',\n",
       " 'hugging',\n",
       " 'pinkhooded',\n",
       " 'stretch',\n",
       " 'bicyclist',\n",
       " 'cross',\n",
       " 'spandex',\n",
       " 'biking',\n",
       " 'jogging',\n",
       " 'headset',\n",
       " 'walkman',\n",
       " 'jogs',\n",
       " 'headphones',\n",
       " 'plant',\n",
       " 'corner',\n",
       " 'bicyclists',\n",
       " 'intersection',\n",
       " 'bikers',\n",
       " 'stop',\n",
       " 'town',\n",
       " 'without',\n",
       " 'guiding',\n",
       " ...]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wordList"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "wordDic = {}\n",
    "for i, word in enumerate(wordList) :\n",
    "    wordDic[word] = i"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1, 2)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wordDic['START'] , wordDic['END']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "Y = []\n",
    "for i in range(len(newCaps)) :\n",
    "    y = [wordDic[word] for word in newCaps[i]]\n",
    "    y.extend(np.zeros(maxLen-len(y) , dtype=np.int32))\n",
    "    # print(y,len(y))\n",
    "    # break\n",
    "    Y.append(y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "Image_Paths = df['image'].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 9999 - 2470519275_65725fd38d.jpg"
     ]
    }
   ],
   "source": [
    "Images = []\n",
    "c = 0 \n",
    "for path in Image_Paths[:10000] :\n",
    "    print(f'\\r {c} - {path}',end='')\n",
    "    img = cv2.imread('Dataset/images/'+path)\n",
    "    img = cv2.resize(img,(64,64))\n",
    "    Images.append(img)\n",
    "    c += 1\n",
    "\n",
    "Images = np.array(Images).astype('float32')/255.0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pickle\n",
    "\n",
    "# dump Images into pickle file\n",
    "with open('Images.pkl','wb') as f:\n",
    "    pickle.dump(Images,f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load pickle\n",
    "import pickle\n",
    "\n",
    "with open('Images.pkl','rb') as f:\n",
    "    Images = pickle.load(f)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "Y= Y[:5000]\n",
    "# Y = np.array(Y)\n",
    "# print(Y.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "  3%|▎         | 168/5000 [00:00<00:02, 1673.64it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 5000/5000 [00:02<00:00, 2352.68it/s]\n"
     ]
    }
   ],
   "source": [
    "X1,X2,y = [],[],[]\n",
    "for i in tqdm(range(5000)):\n",
    "    for j in range(maxLen-1):\n",
    "        X1.append(Images[i])\n",
    "        seq = Y[i][:j+1]\n",
    "        seq.extend(np.zeros(maxLen-len(seq) , dtype=np.int32))\n",
    "        X2.append(seq)\n",
    "        y.append(Y[i][j+1])\n",
    "        # print(X2,y)\n",
    "        # X2 = []\n",
    "    # print(X2,y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "X1 = np.array(X1)\n",
    "X2 = np.array(X2)\n",
    "y = np.array(y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((190000, 64, 64, 3), (190000, 39), (190000,))"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X1.shape,X2.shape,y.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[  1,   0,   0, ...,   0,   0,   0],\n",
       "       [  1,   3,   0, ...,   0,   0,   0],\n",
       "       [  1,   3,   4, ...,   0,   0,   0],\n",
       "       ...,\n",
       "       [  1,   3, 223, ...,   0,   0,   0],\n",
       "       [  1,   3, 223, ...,   0,   0,   0],\n",
       "       [  1,   3, 223, ...,   0,   0,   0]])"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "ename": "",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31mThe Kernel crashed while executing code in the current cell or a previous cell. \n",
      "\u001b[1;31mPlease review the code in the cell(s) to identify a possible cause of the failure. \n",
      "\u001b[1;31mClick <a href='https://aka.ms/vscodeJupyterKernelCrash'>here</a> for more info. \n",
      "\u001b[1;31mView Jupyter <a href='command:jupyter.viewOutput'>log</a> for further details."
     ]
    }
   ],
   "source": [
    "import torch\n",
    "from torch import nn\n",
    "import torch.nn.functional as F\n",
    "from torch.utils.data import DataLoader, TensorDataset\n",
    "\n",
    "\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "from torchsummary import summary\n",
    "from torch.optim.lr_scheduler import StepLR"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, X_val, y_train, y_val = train_test_split(X1, X2, test_size=0.2, random_state=42)\n",
    "\n",
    "print(X_train.shape, y_train.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "X_train_tensor shape: torch.Size([152000, 3, 64, 64])\n",
      "y_train_tensor shape: torch.Size([152000, 39])\n",
      "X_val_tensor shape: torch.Size([38000, 3, 64, 64])\n",
      "y_val_tensor shape: torch.Size([38000, 39])\n"
     ]
    }
   ],
   "source": [
    "# Convert data to PyTorch tensors\n",
    "X_train_tensor = torch.tensor(X_train).permute(0, 3, 1, 2)  # Convert from HWC to CHW format\n",
    "y_train_tensor = torch.tensor(y_train, dtype=torch.float32)\n",
    "X_val_tensor = torch.tensor(X_val).permute(0, 3, 1, 2)\n",
    "y_val_tensor = torch.tensor(y_val, dtype=torch.float32)\n",
    "\n",
    "\n",
    "print(f\"X_train_tensor shape: {X_train_tensor.shape}\")\n",
    "print(f\"y_train_tensor shape: {y_train_tensor.shape}\")\n",
    "print(f\"X_val_tensor shape: {X_val_tensor.shape}\")\n",
    "print(f\"y_val_tensor shape: {y_val_tensor.shape}\")\n",
    "\n",
    "# Create PyTorch DataLoaders\n",
    "train_dataset = TensorDataset(X_train_tensor, y_train_tensor)\n",
    "val_dataset = TensorDataset(X_val_tensor, y_val_tensor)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch\n",
    "import torch.nn as nn\n",
    "import torch.nn.functional as F\n",
    "from torch.utils.data import DataLoader\n",
    "from torch.optim.lr_scheduler import StepLR\n",
    "\n",
    "class CNNRNNModel(nn.Module):\n",
    "    def __init__(self, num_classes=len(wordList),max_len=39):  # Change to 63\n",
    "        super(CNNRNNModel, self).__init__()\n",
    "        \n",
    "        # CNN layers\n",
    "        self.conv1 = nn.Conv2d(in_channels=1, out_channels=32, kernel_size=3, stride=1, padding=1)\n",
    "        self.conv2 = nn.Conv2d(in_channels=32, out_channels=64, kernel_size=3, stride=1, padding=1)\n",
    "        self.conv3 = nn.Conv2d(in_channels=64, out_channels=128, kernel_size=3, stride=1, padding=1)\n",
    "        self.conv4 = nn.Conv2d(in_channels=128, out_channels=256, kernel_size=3, stride=1, padding=1)\n",
    "        self.pool = nn.MaxPool2d(kernel_size=2, stride=2, padding=0)\n",
    "        self.bn1 = nn.BatchNorm2d(32)\n",
    "        self.bn2 = nn.BatchNorm2d(64)\n",
    "        self.bn3 = nn.BatchNorm2d(128)\n",
    "        self.bn4 = nn.BatchNorm2d(256)\n",
    "        \n",
    "        # Fully connected layer to transform CNN output to RNN input\n",
    "        self.fc1 = nn.Linear(256 * 5 * 12, 512*max_len)  # Adjust input size based on final CNN feature map size\n",
    "        \n",
    "        # RNN layers\n",
    "        self.rnn = nn.LSTM(input_size=512, hidden_size=512, num_layers=2, batch_first=True, bidirectional=True)\n",
    "        \n",
    "        # Final fully connected layers\n",
    "        self.fc2 = nn.Linear(1024, 2048)\n",
    "        self.fc3 = nn.Linear(2048, num_classes)\n",
    "        \n",
    "    def forward(self, x):\n",
    "        # CNN forward pass\n",
    "        x = self.pool(F.relu(self.bn1(self.conv1(x))))\n",
    "        x = self.pool(F.relu(self.bn2(self.conv2(x))))\n",
    "        x = self.pool(F.relu(self.bn3(self.conv3(x))))\n",
    "        x = self.pool(F.relu(self.bn4(self.conv4(x))))\n",
    "\n",
    "        # print(x.shape)\n",
    "\n",
    "        # Flatten the output from the CNN\n",
    "        x = x.view(x.size(0), -1)\n",
    "        \n",
    "        # Fully connected layer\n",
    "        x = self.fc1(x)\n",
    "\n",
    "        # print(x.shape)\n",
    "        \n",
    "        # Reshape for RNN input (batch_size, seq_length, input_size)\n",
    "        x = x.view(x.size(0), 6, 512)  # Ensure the sequence length is 6\n",
    "        \n",
    "        # RNN forward pass\n",
    "        x, _ = self.rnn(x)\n",
    "        \n",
    "        # Apply fully connected layers to each time step\n",
    "        x = F.relu(self.fc2(x))\n",
    "        x = F.dropout(x, p=0.5)\n",
    "        x = self.fc3(x)\n",
    "        \n",
    "        return x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def TrainModel(model, train_loader, val_loader, criterion, optimizer, scheduler, batch_size=32, num_epochs=100, patience=10, best_val_loss=float(\"inf\") ):\n",
    "    \n",
    "    train_loader = DataLoader(train_dataset, batch_size=batch_size, shuffle=True)\n",
    "    val_loader = DataLoader(val_dataset, batch_size=batch_size, shuffle=False)\n",
    "\n",
    "    # Training loop\n",
    "    train_losses = []\n",
    "    val_losses = []\n",
    "\n",
    "    device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\n",
    "\n",
    "    for epoch in range(num_epochs):\n",
    "        # Training phase\n",
    "        model.train()\n",
    "        train_loss = 0.0\n",
    "        for i, (images, labels) in enumerate(train_loader):\n",
    "            images, labels = images.to(device), labels.to(device)\n",
    "            \n",
    "            # Forward pass\n",
    "            outputs = model(images)\n",
    "            labels = labels.argmax(2).view(-1)\n",
    "            out_view = outputs.view(-1, len(wordList))\n",
    "            loss = criterion(out_view, labels)\n",
    "            # loss = nn.CTCLoss(blank=62)(outputs.permute(1, 0, 2), labels, torch.full((batch_size,), 6, dtype=torch.long), torch.full((batch_size,), 6, dtype=torch.long))\n",
    "\n",
    "            # Backward and optimize\n",
    "            optimizer.zero_grad()\n",
    "            loss.backward()\n",
    "            optimizer.step()\n",
    "\n",
    "            train_loss += loss.item()\n",
    "\n",
    "            print(f'\\r {i} - {train_loss}',end='')\n",
    "\n",
    "        # Validation phase\n",
    "        model.eval()\n",
    "        val_loss = 0.0\n",
    "        with torch.no_grad():\n",
    "            for images, labels in val_loader:\n",
    "                images, labels = images.to(device), labels.to(device)\n",
    "                \n",
    "                # Forward pass\n",
    "                outputs = model(images)\n",
    "                labels = labels.argmax(2).view(-1)\n",
    "                loss = criterion(outputs.view(-1, len(wordList)), labels)\n",
    "                # loss = nn.CTCLoss(blank=62)(outputs.permute(1, 0, 2), labels, torch.full((batch_size,), 6, dtype=torch.long), torch.full((batch_size,), 6, dtype=torch.long))\n",
    "\n",
    "                val_loss += loss.item()\n",
    "\n",
    "                print(f'\\r {i} - {val_loss}',end=' ')\n",
    "\n",
    "        # Update the learning rate\n",
    "        # scheduler.step(val_loss / len(val_loader))\n",
    "        scheduler.step()\n",
    "\n",
    "        # Save the losses\n",
    "        train_losses.append(train_loss / len(train_loader))\n",
    "        val_losses.append(val_loss / len(val_loader))\n",
    "\n",
    "        # Check for early stopping\n",
    "        if val_loss < best_val_loss:\n",
    "            best_val_loss = val_loss\n",
    "            patience_counter = 0\n",
    "            # Save the best model if required\n",
    "        else:\n",
    "            patience_counter += 1\n",
    "            if patience_counter >= patience:\n",
    "                print(f\"Early stopping at epoch {epoch+1}\")\n",
    "                break\n",
    "\n",
    "        print(f\"\\rEpoch {epoch+1}/{num_epochs}, Train Loss: {train_losses[-1]:.4f}, Val Loss: {val_losses[-1]:.4f}\")\n",
    "\n",
    "    return model, train_losses, val_losses"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cuda\n",
      "CNNRNNModel(\n",
      "  (conv1): Conv2d(1, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
      "  (conv2): Conv2d(32, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
      "  (conv3): Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
      "  (conv4): Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
      "  (pool): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
      "  (bn1): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
      "  (bn2): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
      "  (bn3): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
      "  (bn4): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
      "  (fc1): Linear(in_features=15360, out_features=19968, bias=True)\n",
      "  (rnn): LSTM(512, 512, num_layers=2, batch_first=True, bidirectional=True)\n",
      "  (fc2): Linear(in_features=1024, out_features=2048, bias=True)\n",
      "  (fc3): Linear(in_features=2048, out_features=8831, bias=True)\n",
      ")\n"
     ]
    }
   ],
   "source": [
    "model = CNNRNNModel(num_classes=len(wordList))\n",
    "device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\n",
    "print(device)\n",
    "model.to(device)\n",
    "\n",
    "print(model)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "ename": "RuntimeError",
     "evalue": "Input type (unsigned char) and bias type (float) should be the same",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mRuntimeError\u001b[0m                              Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[42], line 6\u001b[0m\n\u001b[1;32m      3\u001b[0m optimizer \u001b[38;5;241m=\u001b[39m torch\u001b[38;5;241m.\u001b[39moptim\u001b[38;5;241m.\u001b[39mAdam(model\u001b[38;5;241m.\u001b[39mparameters(), lr\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m0.0001\u001b[39m)\n\u001b[1;32m      4\u001b[0m scheduler \u001b[38;5;241m=\u001b[39m StepLR(optimizer, step_size\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m10\u001b[39m, gamma\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m0.9\u001b[39m)\n\u001b[0;32m----> 6\u001b[0m model, train_losses, val_losses \u001b[38;5;241m=\u001b[39m \u001b[43mTrainModel\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmodel\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtrain_dataset\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mval_dataset\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcriterion\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43moptimizer\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mscheduler\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbatch_size\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m32\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mnum_epochs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m100\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpatience\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m10\u001b[39;49m\u001b[43m)\u001b[49m\n",
      "Cell \u001b[0;32mIn[39], line 20\u001b[0m, in \u001b[0;36mTrainModel\u001b[0;34m(model, train_loader, val_loader, criterion, optimizer, scheduler, batch_size, num_epochs, patience, best_val_loss)\u001b[0m\n\u001b[1;32m     17\u001b[0m images, labels \u001b[38;5;241m=\u001b[39m images\u001b[38;5;241m.\u001b[39mto(device), labels\u001b[38;5;241m.\u001b[39mto(device)\n\u001b[1;32m     19\u001b[0m \u001b[38;5;66;03m# Forward pass\u001b[39;00m\n\u001b[0;32m---> 20\u001b[0m outputs \u001b[38;5;241m=\u001b[39m \u001b[43mmodel\u001b[49m\u001b[43m(\u001b[49m\u001b[43mimages\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     21\u001b[0m labels \u001b[38;5;241m=\u001b[39m labels\u001b[38;5;241m.\u001b[39margmax(\u001b[38;5;241m2\u001b[39m)\u001b[38;5;241m.\u001b[39mview(\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m)\n\u001b[1;32m     22\u001b[0m out_view \u001b[38;5;241m=\u001b[39m outputs\u001b[38;5;241m.\u001b[39mview(\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m, \u001b[38;5;28mlen\u001b[39m(wordList))\n",
      "File \u001b[0;32m~/anaconda3/envs/AI/lib/python3.10/site-packages/torch/nn/modules/module.py:1532\u001b[0m, in \u001b[0;36mModule._wrapped_call_impl\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m   1530\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_compiled_call_impl(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)  \u001b[38;5;66;03m# type: ignore[misc]\u001b[39;00m\n\u001b[1;32m   1531\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 1532\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_call_impl\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/anaconda3/envs/AI/lib/python3.10/site-packages/torch/nn/modules/module.py:1541\u001b[0m, in \u001b[0;36mModule._call_impl\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m   1536\u001b[0m \u001b[38;5;66;03m# If we don't have any hooks, we want to skip the rest of the logic in\u001b[39;00m\n\u001b[1;32m   1537\u001b[0m \u001b[38;5;66;03m# this function, and just call forward.\u001b[39;00m\n\u001b[1;32m   1538\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m (\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_backward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_backward_pre_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_forward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_forward_pre_hooks\n\u001b[1;32m   1539\u001b[0m         \u001b[38;5;129;01mor\u001b[39;00m _global_backward_pre_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_backward_hooks\n\u001b[1;32m   1540\u001b[0m         \u001b[38;5;129;01mor\u001b[39;00m _global_forward_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_forward_pre_hooks):\n\u001b[0;32m-> 1541\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mforward_call\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1543\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m   1544\u001b[0m     result \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n",
      "Cell \u001b[0;32mIn[38], line 34\u001b[0m, in \u001b[0;36mCNNRNNModel.forward\u001b[0;34m(self, x)\u001b[0m\n\u001b[1;32m     32\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mforward\u001b[39m(\u001b[38;5;28mself\u001b[39m, x):\n\u001b[1;32m     33\u001b[0m     \u001b[38;5;66;03m# CNN forward pass\u001b[39;00m\n\u001b[0;32m---> 34\u001b[0m     x \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mpool(F\u001b[38;5;241m.\u001b[39mrelu(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mbn1(\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mconv1\u001b[49m\u001b[43m(\u001b[49m\u001b[43mx\u001b[49m\u001b[43m)\u001b[49m)))\n\u001b[1;32m     35\u001b[0m     x \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mpool(F\u001b[38;5;241m.\u001b[39mrelu(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mbn2(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mconv2(x))))\n\u001b[1;32m     36\u001b[0m     x \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mpool(F\u001b[38;5;241m.\u001b[39mrelu(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mbn3(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mconv3(x))))\n",
      "File \u001b[0;32m~/anaconda3/envs/AI/lib/python3.10/site-packages/torch/nn/modules/module.py:1532\u001b[0m, in \u001b[0;36mModule._wrapped_call_impl\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m   1530\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_compiled_call_impl(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)  \u001b[38;5;66;03m# type: ignore[misc]\u001b[39;00m\n\u001b[1;32m   1531\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 1532\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_call_impl\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/anaconda3/envs/AI/lib/python3.10/site-packages/torch/nn/modules/module.py:1541\u001b[0m, in \u001b[0;36mModule._call_impl\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m   1536\u001b[0m \u001b[38;5;66;03m# If we don't have any hooks, we want to skip the rest of the logic in\u001b[39;00m\n\u001b[1;32m   1537\u001b[0m \u001b[38;5;66;03m# this function, and just call forward.\u001b[39;00m\n\u001b[1;32m   1538\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m (\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_backward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_backward_pre_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_forward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_forward_pre_hooks\n\u001b[1;32m   1539\u001b[0m         \u001b[38;5;129;01mor\u001b[39;00m _global_backward_pre_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_backward_hooks\n\u001b[1;32m   1540\u001b[0m         \u001b[38;5;129;01mor\u001b[39;00m _global_forward_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_forward_pre_hooks):\n\u001b[0;32m-> 1541\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mforward_call\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1543\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m   1544\u001b[0m     result \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n",
      "File \u001b[0;32m~/anaconda3/envs/AI/lib/python3.10/site-packages/torch/nn/modules/conv.py:460\u001b[0m, in \u001b[0;36mConv2d.forward\u001b[0;34m(self, input)\u001b[0m\n\u001b[1;32m    459\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mforward\u001b[39m(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;28minput\u001b[39m: Tensor) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m Tensor:\n\u001b[0;32m--> 460\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_conv_forward\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43minput\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mweight\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mbias\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/anaconda3/envs/AI/lib/python3.10/site-packages/torch/nn/modules/conv.py:456\u001b[0m, in \u001b[0;36mConv2d._conv_forward\u001b[0;34m(self, input, weight, bias)\u001b[0m\n\u001b[1;32m    452\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mpadding_mode \u001b[38;5;241m!=\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mzeros\u001b[39m\u001b[38;5;124m'\u001b[39m:\n\u001b[1;32m    453\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m F\u001b[38;5;241m.\u001b[39mconv2d(F\u001b[38;5;241m.\u001b[39mpad(\u001b[38;5;28minput\u001b[39m, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_reversed_padding_repeated_twice, mode\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mpadding_mode),\n\u001b[1;32m    454\u001b[0m                     weight, bias, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mstride,\n\u001b[1;32m    455\u001b[0m                     _pair(\u001b[38;5;241m0\u001b[39m), \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdilation, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mgroups)\n\u001b[0;32m--> 456\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mF\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mconv2d\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43minput\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mweight\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbias\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mstride\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    457\u001b[0m \u001b[43m                \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mpadding\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdilation\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mgroups\u001b[49m\u001b[43m)\u001b[49m\n",
      "\u001b[0;31mRuntimeError\u001b[0m: Input type (unsigned char) and bias type (float) should be the same"
     ]
    }
   ],
   "source": [
    "# Train the model\n",
    "criterion = nn.CrossEntropyLoss()\n",
    "optimizer = torch.optim.Adam(model.parameters(), lr=0.0001)\n",
    "scheduler = StepLR(optimizer, step_size=10, gamma=0.9)\n",
    "\n",
    "model, train_losses, val_losses = TrainModel(model, train_dataset, val_dataset, criterion, optimizer, scheduler, batch_size=32, num_epochs=100, patience=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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