Extracting_text_from_images_tesseract.ipynb

extracting_text_from_images_tesseract.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Extracting_text_from_images_tesseract.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "display_name": "Python 3",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.6.10"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/gist/sai-teja-ponugoti/6eb76a25dc1d6e0ec1de6165748a77f4/extracting_text_from_images_tesseract.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "fsZspRI6j92d"
      },
      "source": [
        "In this notebook we will demonstrate how to use tesseract to extract text from images"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "_paRSCL_io1T",
        "colab": {}
      },
      "source": [
        "# installing required librareis\n",
        "!sudo apt install tesseract-ocr\n",
        "!pip install pytesseract"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "m7LavpYEivma",
        "colab": {}
      },
      "source": [
        "#making the necessary imports\n",
        "import pytesseract\n",
        "from pytesseract import image_to_string\n",
        "from PIL import Image"
      ],
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "a0TcLABSi5g-",
        "colab": {
          "resources": {
            "http://localhost:8080/nbextensions/google.colab/files.js": {
              "data": 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              "ok": true,
              "headers": [
                [
                  "content-type",
                  "application/javascript"
                ]
              ],
              "status": 200,
              "status_text": ""
            }
          },
          "base_uri": "https://localhost:8080/",
          "height": 72
        },
        "outputId": "4ba16879-cbc6-4dd2-a377-3c00b0915c59"
      },
      "source": [
        "#uploading an image into colab\n",
        "from google.colab import files\n",
        "uploaded = files.upload()"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "\n",
              "     <input type=\"file\" id=\"files-e3eb7dec-c5eb-4a9e-92b4-362dadceeadc\" name=\"files[]\" multiple disabled\n",
              "        style=\"border:none\" />\n",
              "     <output id=\"result-e3eb7dec-c5eb-4a9e-92b4-362dadceeadc\">\n",
              "      Upload widget is only available when the cell has been executed in the\n",
              "      current browser session. Please rerun this cell to enable.\n",
              "      </output>\n",
              "      <script src=\"/nbextensions/google.colab/files.js\"></script> "
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Saving Pytesseract.png to Pytesseract (1).png\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "cLD97k855DEF",
        "colab_type": "text"
      },
      "source": [
        "used image :\n",
        "\n",
        "![alt text](https://drive.google.com/uc?export=view&id=1VktTQUEevEy1pF6UWfKx9mvQSpDlCj1U)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "IncbndQPjN-D",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 52
        },
        "outputId": "6d63a93e-5252-4b26-fa98-143f177b4328"
      },
      "source": [
        "# extracting content from the image\n",
        "extractedInformation = image_to_string(Image.open(\"Pytesseract.png\"))\n",
        "extractedInformation"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "application/vnd.google.colaboratory.intrinsic": {
              "type": "string"
            },
            "text/plain": [
              "'Pytesseract: Get started with OCR. Optical Character Recognition (OCR) is a system\\nthat provides a full alphanumeric character recognition on an image. The system allows\\nextracting text from an image, to convert it later into an editable file. may 21, 2019'"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "-tkNw6SClGbb"
      },
      "source": [
        "As you can see the output seems to be quiet good."
      ]
    }
  ]
}