How_to_upload_an_image_to_Colab_.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "How to upload an image to Colab .ipynb",
      "provenance": [],
      "toc_visible": true,
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/vyz1194/vyz/blob/master/How_to_upload_an_image_to_Colab_.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "FoHsQnTVPyqM"
      },
      "source": [
        "#How to upload an image to Colab?"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ryAQC-3gP0qC"
      },
      "source": [
        "# Use libraries\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RPVqkNhgPlv0"
      },
      "source": [
        "from google.colab import files\n",
        "from IPython.display import Image"
      ],
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oXd5i9OvQN5p",
        "outputId": "ed83f99b-4410-4d6d-a5f6-e4e837fddbf7",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 73
        }
      },
      "source": [
        "uploaded = files.upload()"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "\n",
              "     <input type=\"file\" id=\"files-c7b2afdc-a18a-4069-be25-67d7f8116943\" name=\"files[]\" multiple disabled\n",
              "        style=\"border:none\" />\n",
              "     <output id=\"result-c7b2afdc-a18a-4069-be25-67d7f8116943\">\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>// Copyright 2017 Google LLC\n",
              "//\n",
              "// Licensed under the Apache License, Version 2.0 (the \"License\");\n",
              "// you may not use this file except in compliance with the License.\n",
              "// You may obtain a copy of the License at\n",
              "//\n",
              "//      http://www.apache.org/licenses/LICENSE-2.0\n",
              "//\n",
              "// Unless required by applicable law or agreed to in writing, software\n",
              "// distributed under the License is distributed on an \"AS IS\" BASIS,\n",
              "// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
              "// See the License for the specific language governing permissions and\n",
              "// limitations under the License.\n",
              "\n",
              "/**\n",
              " * @fileoverview Helpers for google.colab Python module.\n",
              " */\n",
              "(function(scope) {\n",
              "function span(text, styleAttributes = {}) {\n",
              "  const element = document.createElement('span');\n",
              "  element.textContent = text;\n",
              "  for (const key of Object.keys(styleAttributes)) {\n",
              "    element.style[key] = styleAttributes[key];\n",
              "  }\n",
              "  return element;\n",
              "}\n",
              "\n",
              "// Max number of bytes which will be uploaded at a time.\n",
              "const MAX_PAYLOAD_SIZE = 100 * 1024;\n",
              "\n",
              "function _uploadFiles(inputId, outputId) {\n",
              "  const steps = uploadFilesStep(inputId, outputId);\n",
              "  const outputElement = document.getElementById(outputId);\n",
              "  // Cache steps on the outputElement to make it available for the next call\n",
              "  // to uploadFilesContinue from Python.\n",
              "  outputElement.steps = steps;\n",
              "\n",
              "  return _uploadFilesContinue(outputId);\n",
              "}\n",
              "\n",
              "// This is roughly an async generator (not supported in the browser yet),\n",
              "// where there are multiple asynchronous steps and the Python side is going\n",
              "// to poll for completion of each step.\n",
              "// This uses a Promise to block the python side on completion of each step,\n",
              "// then passes the result of the previous step as the input to the next step.\n",
              "function _uploadFilesContinue(outputId) {\n",
              "  const outputElement = document.getElementById(outputId);\n",
              "  const steps = outputElement.steps;\n",
              "\n",
              "  const next = steps.next(outputElement.lastPromiseValue);\n",
              "  return Promise.resolve(next.value.promise).then((value) => {\n",
              "    // Cache the last promise value to make it available to the next\n",
              "    // step of the generator.\n",
              "    outputElement.lastPromiseValue = value;\n",
              "    return next.value.response;\n",
              "  });\n",
              "}\n",
              "\n",
              "/**\n",
              " * Generator function which is called between each async step of the upload\n",
              " * process.\n",
              " * @param {string} inputId Element ID of the input file picker element.\n",
              " * @param {string} outputId Element ID of the output display.\n",
              " * @return {!Iterable<!Object>} Iterable of next steps.\n",
              " */\n",
              "function* uploadFilesStep(inputId, outputId) {\n",
              "  const inputElement = document.getElementById(inputId);\n",
              "  inputElement.disabled = false;\n",
              "\n",
              "  const outputElement = document.getElementById(outputId);\n",
              "  outputElement.innerHTML = '';\n",
              "\n",
              "  const pickedPromise = new Promise((resolve) => {\n",
              "    inputElement.addEventListener('change', (e) => {\n",
              "      resolve(e.target.files);\n",
              "    });\n",
              "  });\n",
              "\n",
              "  const cancel = document.createElement('button');\n",
              "  inputElement.parentElement.appendChild(cancel);\n",
              "  cancel.textContent = 'Cancel upload';\n",
              "  const cancelPromise = new Promise((resolve) => {\n",
              "    cancel.onclick = () => {\n",
              "      resolve(null);\n",
              "    };\n",
              "  });\n",
              "\n",
              "  // Wait for the user to pick the files.\n",
              "  const files = yield {\n",
              "    promise: Promise.race([pickedPromise, cancelPromise]),\n",
              "    response: {\n",
              "      action: 'starting',\n",
              "    }\n",
              "  };\n",
              "\n",
              "  cancel.remove();\n",
              "\n",
              "  // Disable the input element since further picks are not allowed.\n",
              "  inputElement.disabled = true;\n",
              "\n",
              "  if (!files) {\n",
              "    return {\n",
              "      response: {\n",
              "        action: 'complete',\n",
              "      }\n",
              "    };\n",
              "  }\n",
              "\n",
              "  for (const file of files) {\n",
              "    const li = document.createElement('li');\n",
              "    li.append(span(file.name, {fontWeight: 'bold'}));\n",
              "    li.append(span(\n",
              "        `(${file.type || 'n/a'}) - ${file.size} bytes, ` +\n",
              "        `last modified: ${\n",
              "            file.lastModifiedDate ? file.lastModifiedDate.toLocaleDateString() :\n",
              "                                    'n/a'} - `));\n",
              "    const percent = span('0% done');\n",
              "    li.appendChild(percent);\n",
              "\n",
              "    outputElement.appendChild(li);\n",
              "\n",
              "    const fileDataPromise = new Promise((resolve) => {\n",
              "      const reader = new FileReader();\n",
              "      reader.onload = (e) => {\n",
              "        resolve(e.target.result);\n",
              "      };\n",
              "      reader.readAsArrayBuffer(file);\n",
              "    });\n",
              "    // Wait for the data to be ready.\n",
              "    let fileData = yield {\n",
              "      promise: fileDataPromise,\n",
              "      response: {\n",
              "        action: 'continue',\n",
              "      }\n",
              "    };\n",
              "\n",
              "    // Use a chunked sending to avoid message size limits. See b/62115660.\n",
              "    let position = 0;\n",
              "    do {\n",
              "      const length = Math.min(fileData.byteLength - position, MAX_PAYLOAD_SIZE);\n",
              "      const chunk = new Uint8Array(fileData, position, length);\n",
              "      position += length;\n",
              "\n",
              "      const base64 = btoa(String.fromCharCode.apply(null, chunk));\n",
              "      yield {\n",
              "        response: {\n",
              "          action: 'append',\n",
              "          file: file.name,\n",
              "          data: base64,\n",
              "        },\n",
              "      };\n",
              "\n",
              "      let percentDone = fileData.byteLength === 0 ?\n",
              "          100 :\n",
              "          Math.round((position / fileData.byteLength) * 100);\n",
              "      percent.textContent = `${percentDone}% done`;\n",
              "\n",
              "    } while (position < fileData.byteLength);\n",
              "  }\n",
              "\n",
              "  // All done.\n",
              "  yield {\n",
              "    response: {\n",
              "      action: 'complete',\n",
              "    }\n",
              "  };\n",
              "}\n",
              "\n",
              "scope.google = scope.google || {};\n",
              "scope.google.colab = scope.google.colab || {};\n",
              "scope.google.colab._files = {\n",
              "  _uploadFiles,\n",
              "  _uploadFilesContinue,\n",
              "};\n",
              "})(self);\n",
              "</script> "
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Saving ticket.jpg to ticket.jpg\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "Image('ticket.jpg')"
      ],
      "metadata": {
        "id": "3dpYPZx_CHn2",
        "outputId": "c709c13f-6b7d-4bc4-d87f-c6d99a933c68",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 170
        }
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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\n",
            "text/plain": [
              "<IPython.core.display.Image object>"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "e3RuLhrCQbzI"
      },
      "source": [
        "ticket=Image('ticket.jpg')"
      ],
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install pytesseract\n",
        "!apt-get install tesseract-ocr"
      ],
      "metadata": {
        "id": "NmCdN6lXB7E8",
        "outputId": "7c07c85c-8024-44db-a19e-82cfdb271037",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting pytesseract\n",
            "  Downloading pytesseract-0.3.10-py3-none-any.whl (14 kB)\n",
            "Requirement already satisfied: packaging>=21.3 in /usr/local/lib/python3.10/dist-packages (from pytesseract) (23.1)\n",
            "Requirement already satisfied: Pillow>=8.0.0 in /usr/local/lib/python3.10/dist-packages (from pytesseract) (9.4.0)\n",
            "Installing collected packages: pytesseract\n",
            "Successfully installed pytesseract-0.3.10\n",
            "Reading package lists... Done\n",
            "Building dependency tree... Done\n",
            "Reading state information... Done\n",
            "The following additional packages will be installed:\n",
            "  tesseract-ocr-eng tesseract-ocr-osd\n",
            "The following NEW packages will be installed:\n",
            "  tesseract-ocr tesseract-ocr-eng tesseract-ocr-osd\n",
            "0 upgraded, 3 newly installed, 0 to remove and 16 not upgraded.\n",
            "Need to get 4,816 kB of archives.\n",
            "After this operation, 15.6 MB of additional disk space will be used.\n",
            "Get:1 http://archive.ubuntu.com/ubuntu jammy/universe amd64 tesseract-ocr-eng all 1:4.00~git30-7274cfa-1.1 [1,591 kB]\n",
            "Get:2 http://archive.ubuntu.com/ubuntu jammy/universe amd64 tesseract-ocr-osd all 1:4.00~git30-7274cfa-1.1 [2,990 kB]\n",
            "Get:3 http://archive.ubuntu.com/ubuntu jammy/universe amd64 tesseract-ocr amd64 4.1.1-2.1build1 [236 kB]\n",
            "Fetched 4,816 kB in 1s (4,205 kB/s)\n",
            "Selecting previously unselected package tesseract-ocr-eng.\n",
            "(Reading database ... 120831 files and directories currently installed.)\n",
            "Preparing to unpack .../tesseract-ocr-eng_1%3a4.00~git30-7274cfa-1.1_all.deb ...\n",
            "Unpacking tesseract-ocr-eng (1:4.00~git30-7274cfa-1.1) ...\n",
            "Selecting previously unselected package tesseract-ocr-osd.\n",
            "Preparing to unpack .../tesseract-ocr-osd_1%3a4.00~git30-7274cfa-1.1_all.deb ...\n",
            "Unpacking tesseract-ocr-osd (1:4.00~git30-7274cfa-1.1) ...\n",
            "Selecting previously unselected package tesseract-ocr.\n",
            "Preparing to unpack .../tesseract-ocr_4.1.1-2.1build1_amd64.deb ...\n",
            "Unpacking tesseract-ocr (4.1.1-2.1build1) ...\n",
            "Setting up tesseract-ocr-eng (1:4.00~git30-7274cfa-1.1) ...\n",
            "Setting up tesseract-ocr-osd (1:4.00~git30-7274cfa-1.1) ...\n",
            "Setting up tesseract-ocr (4.1.1-2.1build1) ...\n",
            "Processing triggers for man-db (2.10.2-1) ...\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#convert image to png if neeeded\n",
        "import PIL\n",
        "\n",
        "# Read the JPG image\n",
        "image = PIL.Image.open('ticket.jpg')\n",
        "\n",
        "# Convert the image to PNG\n",
        "image.save('ticket.png')"
      ],
      "metadata": {
        "id": "59Osd81sCx3I"
      },
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "ticket= PIL.Image.open('ticket.png')"
      ],
      "metadata": {
        "id": "m13QxzG-C7u_"
      },
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tjXKuh9mQv_6",
        "outputId": "42ae6e31-076d-4a48-a48d-8c11566e06b4",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "import pytesseract\n",
        "from PIL import Image\n",
        "\n",
        "\n",
        "\n",
        "# Extract the text from the image\n",
        "extracted_text = pytesseract.image_to_string(ticket)\n",
        "\n",
        "# Print the text\n",
        "print(extracted_text)"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            " \n",
            "\n",
            " \n",
            "\f\n"
          ]
        }
      ]
    }
  ]
}