Extract text.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import cv2\n",
    "import pytesseract\n",
    "from PIL import Image\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "text = pytesseract.image_to_string(Image.open('/Users/askvyas/Desktop/001.jpg'))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'TOI LOU WL\\n\\n \\n\\nrT TC 7'"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "text"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "image = cv2.imread('/Users/askvyas/Desktop/001.jpg')\n",
    "gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "cv2.imshow(\"\",gray)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "text2 = pytesseract.image_to_string(gray)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'MALI!\\n\\ni -\\n\\nUs\\n\\n    \\n  \\n\\n  \\n\\n3\\n\\n& ae p a\\nWHAT YOU THINK IT MEMES}'"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "text2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "import pandas as pd\n",
    "import re\n",
    "import string\n",
    "def clean_text(text):\n",
    "    \n",
    "    ## Remove puncuation\n",
    "    text = text.translate(string.punctuation)\n",
    "    \n",
    "    ## Convert words to lower case and split them\n",
    "    text = text.lower()\n",
    "    \n",
    "    ## Remove stop words\n",
    "    ## Clean the text\n",
    "    text = re.sub(r\"[^A-Za-z0-9^,!.\\/'+-=]\", \" \", text)\n",
    "    text = re.sub(r\"what's\", \"what is \", text)\n",
    "    text = re.sub(r\"\\'s\", \" \", text)\n",
    "    text = re.sub(r\"\\'ve\", \" have \", text)\n",
    "    text = re.sub(r\"n't\", \" not \", text)\n",
    "    text = re.sub(r\"i'm\", \"i am \", text)\n",
    "    text = re.sub(r\"\\'re\", \" are \", text)\n",
    "    text = re.sub(r\"\\'d\", \" would \", text)\n",
    "    text = re.sub(r\"\\'ll\", \" will \", text)\n",
    "    text = re.sub(r\",\", \" \", text)\n",
    "    text = re.sub(r\"\\.\", \" \", text)\n",
    "    text = re.sub(r\"!\", \"  \", text)\n",
    "    text = re.sub(r\"\\/\", \" \", text)\n",
    "    text = re.sub(r\"\\^\", \"  \", text)\n",
    "    text = re.sub(r\"\\+\", \"  \", text)\n",
    "    text = re.sub(r\"\\-\", \"  \", text)\n",
    "    text = re.sub(r\"\\=\", \"  \", text)\n",
    "    text = re.sub(r\"'\", \" \", text)\n",
    "    text = re.sub(r\"(\\d+)(k)\", r\"\\g<1>000\", text)\n",
    "    text = re.sub(r\":\", \" : \", text)\n",
    "    text = re.sub(r\" e g \", \" eg \", text)\n",
    "    text = re.sub(r\" b g \", \" bg \", text)\n",
    "    text = re.sub(r\"\\0s\", \"0\", text)\n",
    "    text = re.sub(r\" 9 11 \", \"911\", text)\n",
    "    text = re.sub(r\"e - mail\", \"email\", text)\n",
    "    text = re.sub(r\"\\s{2,}\", \" \", text)\n",
    "    return text\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mali i us 3 ae p a what you think it memes \n"
     ]
    }
   ],
   "source": [
    "print(str(clean_text(text2)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.7"
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 },
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}