Upload PDF_TO_EXCEL_By_Neuralearn_.ipynb

PDF_TO_EXCEL_By_Neuralearn_.ipynb

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+{
+  "cells": [
+    {
+      "cell_type": "code",
+      "source": [
+        "from PIL import Image\n",
+        "import cv2\n",
+        "import numpy as np\n",
+        "import pandas as pd\n",
+        "import tensorflow as tf"
+      ],
+      "metadata": {
+        "id": "mhEjVUbiUytV"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "#!pip install paddlepaddle-gpu==2.3.2 cudatoolkit==10.2"
+      ],
+      "metadata": {
+        "id": "JejuCeNXHckg"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "!pip install paddlepaddle-gpu==2.3.0.post110 -f https://www.paddlepaddle.org.cn/whl/linux/mkl/avx/stable.html"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "xWhdOt9Jay6z",
+        "outputId": "cda3179f-f1d6-41e3-bdd2-6d8fdeab5867"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
+            "Looking in links: https://www.paddlepaddle.org.cn/whl/linux/mkl/avx/stable.html\n",
+            "Collecting paddlepaddle-gpu==2.3.0.post110\n",
+            "  Downloading https://paddle-wheel.bj.bcebos.com/2.3.0/linux/linux-gpu-cuda11.0-cudnn8-mkl-gcc8.2-avx/paddlepaddle_gpu-2.3.0.post110-cp37-cp37m-linux_x86_64.whl (532.9 MB)\n",
+            "\u001b[K     |████████████████████████████████| 532.9 MB 27 kB/s \n",
+            "\u001b[?25hRequirement already satisfied: decorator in /usr/local/lib/python3.7/dist-packages (from paddlepaddle-gpu==2.3.0.post110) (4.4.2)\n",
+            "Requirement already satisfied: Pillow in /usr/local/lib/python3.7/dist-packages (from paddlepaddle-gpu==2.3.0.post110) (7.1.2)\n",
+            "Requirement already satisfied: requests>=2.20.0 in /usr/local/lib/python3.7/dist-packages (from paddlepaddle-gpu==2.3.0.post110) (2.23.0)\n",
+            "Collecting paddle-bfloat==0.1.2\n",
+            "  Downloading paddle_bfloat-0.1.2-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (373 kB)\n",
+            "\u001b[K     |████████████████████████████████| 373 kB 5.7 MB/s \n",
+            "\u001b[?25hRequirement already satisfied: six in /usr/local/lib/python3.7/dist-packages (from paddlepaddle-gpu==2.3.0.post110) (1.15.0)\n",
+            "Requirement already satisfied: protobuf>=3.1.0 in /usr/local/lib/python3.7/dist-packages (from paddlepaddle-gpu==2.3.0.post110) (3.19.6)\n",
+            "Requirement already satisfied: astor in /usr/local/lib/python3.7/dist-packages (from paddlepaddle-gpu==2.3.0.post110) (0.8.1)\n",
+            "Requirement already satisfied: numpy>=1.13 in /usr/local/lib/python3.7/dist-packages (from paddlepaddle-gpu==2.3.0.post110) (1.21.6)\n",
+            "Requirement already satisfied: opt-einsum==3.3.0 in /usr/local/lib/python3.7/dist-packages (from paddlepaddle-gpu==2.3.0.post110) (3.3.0)\n",
+            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests>=2.20.0->paddlepaddle-gpu==2.3.0.post110) (2022.9.24)\n",
+            "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests>=2.20.0->paddlepaddle-gpu==2.3.0.post110) (2.10)\n",
+            "Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests>=2.20.0->paddlepaddle-gpu==2.3.0.post110) (1.24.3)\n",
+            "Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests>=2.20.0->paddlepaddle-gpu==2.3.0.post110) (3.0.4)\n",
+            "Installing collected packages: paddle-bfloat, paddlepaddle-gpu\n",
+            "Successfully installed paddle-bfloat-0.1.2 paddlepaddle-gpu-2.3.0.post110\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "dvKiMyj2feUe"
+      },
+      "source": [
+        "# pdf2image"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "## Installation"
+      ],
+      "metadata": {
+        "id": "aIz56VvlWkf-"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "!pip install pdf2image\n",
+        "!apt-get update\n",
+        "!apt-get install poppler-utils"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "biSgyAkWnUD3",
+        "outputId": "06487f1d-40ee-4de6-f072-6372561d16cd"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
+            "Collecting pdf2image\n",
+            "  Downloading pdf2image-1.16.0-py3-none-any.whl (10 kB)\n",
+            "Requirement already satisfied: pillow in /usr/local/lib/python3.7/dist-packages (from pdf2image) (7.1.2)\n",
+            "Installing collected packages: pdf2image\n",
+            "Successfully installed pdf2image-1.16.0\n",
+            "Get:1 https://cloud.r-project.org/bin/linux/ubuntu bionic-cran40/ InRelease [3,626 B]\n",
+            "Ign:2 https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64  InRelease\n",
+            "Hit:3 https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64  InRelease\n",
+            "Hit:4 https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64  Release\n",
+            "Hit:5 http://archive.ubuntu.com/ubuntu bionic InRelease\n",
+            "Get:6 http://ppa.launchpad.net/c2d4u.team/c2d4u4.0+/ubuntu bionic InRelease [15.9 kB]\n",
+            "Get:7 http://archive.ubuntu.com/ubuntu bionic-updates InRelease [88.7 kB]\n",
+            "Get:8 http://security.ubuntu.com/ubuntu bionic-security InRelease [88.7 kB]\n",
+            "Hit:10 http://ppa.launchpad.net/cran/libgit2/ubuntu bionic InRelease\n",
+            "Get:11 http://archive.ubuntu.com/ubuntu bionic-backports InRelease [83.3 kB]\n",
+            "Hit:12 http://ppa.launchpad.net/deadsnakes/ppa/ubuntu bionic InRelease\n",
+            "Hit:13 http://ppa.launchpad.net/graphics-drivers/ppa/ubuntu bionic InRelease\n",
+            "Get:14 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 Packages [3,494 kB]\n",
+            "Get:15 http://ppa.launchpad.net/c2d4u.team/c2d4u4.0+/ubuntu bionic/main Sources [2,225 kB]\n",
+            "Get:16 http://security.ubuntu.com/ubuntu bionic-security/main amd64 Packages [3,068 kB]\n",
+            "Get:17 http://archive.ubuntu.com/ubuntu bionic-updates/multiverse amd64 Packages [29.8 kB]\n",
+            "Get:18 http://archive.ubuntu.com/ubuntu bionic-updates/restricted amd64 Packages [1,303 kB]\n",
+            "Get:19 http://archive.ubuntu.com/ubuntu bionic-updates/universe amd64 Packages [2,336 kB]\n",
+            "Get:20 http://security.ubuntu.com/ubuntu bionic-security/universe amd64 Packages [1,561 kB]\n",
+            "Get:21 http://ppa.launchpad.net/c2d4u.team/c2d4u4.0+/ubuntu bionic/main amd64 Packages [1,138 kB]\n",
+            "Fetched 15.4 MB in 4s (3,448 kB/s)\n",
+            "Reading package lists... Done\n",
+            "Reading package lists... Done\n",
+            "Building dependency tree       \n",
+            "Reading state information... Done\n",
+            "The following package was automatically installed and is no longer required:\n",
+            "  libnvidia-common-460\n",
+            "Use 'apt autoremove' to remove it.\n",
+            "The following NEW packages will be installed:\n",
+            "  poppler-utils\n",
+            "0 upgraded, 1 newly installed, 0 to remove and 7 not upgraded.\n",
+            "Need to get 154 kB of archives.\n",
+            "After this operation, 613 kB of additional disk space will be used.\n",
+            "Get:1 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 poppler-utils amd64 0.62.0-2ubuntu2.14 [154 kB]\n",
+            "Fetched 154 kB in 1s (198 kB/s)\n",
+            "Selecting previously unselected package poppler-utils.\n",
+            "(Reading database ... 123991 files and directories currently installed.)\n",
+            "Preparing to unpack .../poppler-utils_0.62.0-2ubuntu2.14_amd64.deb ...\n",
+            "Unpacking poppler-utils (0.62.0-2ubuntu2.14) ...\n",
+            "Setting up poppler-utils (0.62.0-2ubuntu2.14) ...\n",
+            "Processing triggers for man-db (2.8.3-2ubuntu0.1) ...\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "## Conversion"
+      ],
+      "metadata": {
+        "id": "pLaguCz1WmF9"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "from pdf2image import convert_from_path"
+      ],
+      "metadata": {
+        "id": "HI1dzCGmkeWI"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "images = convert_from_path('/content/bahdanau attention.pdf')"
+      ],
+      "metadata": {
+        "id": "xyhjFgqjkgG7"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "!mkdir pages"
+      ],
+      "metadata": {
+        "id": "M5hBWxpskgJW"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "for i in range(len(images)):\n",
+        "  images[i].save('pages/page'+str(i)+'.jpg', 'JPEG')"
+      ],
+      "metadata": {
+        "id": "7mlH9ltkkgMB"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "# Layout"
+      ],
+      "metadata": {
+        "id": "Urwb7Q_OZC8t"
+      }
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "## Installation"
+      ],
+      "metadata": {
+        "id": "vTkwQbF4FZPN"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "#!python3 -m pip install paddlepaddle-gpu\n",
+        "!pip install \"paddleocr>=2.0.1\"\n",
+        "!pip install protobuf==3.20.0\n",
+        "!git clone https://github.com/PaddlePaddle/PaddleOCR.git"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 1000
+        },
+        "id": "R0lRpQLkIpbZ",
+        "outputId": "24283e8e-5de0-4b41-bb43-8d0638f927c1"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
+            "Collecting paddleocr>=2.0.1\n",
+            "  Downloading paddleocr-2.6.1.0-py3-none-any.whl (409 kB)\n",
+            "\u001b[K     |████████████████████████████████| 409 kB 6.1 MB/s \n",
+            "\u001b[?25hRequirement already satisfied: lmdb in /usr/local/lib/python3.7/dist-packages (from paddleocr>=2.0.1) (0.99)\n",
+            "Requirement already satisfied: tqdm in /usr/local/lib/python3.7/dist-packages (from paddleocr>=2.0.1) (4.64.1)\n",
+            "Collecting python-docx\n",
+            "  Downloading python-docx-0.8.11.tar.gz (5.6 MB)\n",
+            "\u001b[K     |████████████████████████████████| 5.6 MB 56.9 MB/s \n",
+            "\u001b[?25hCollecting premailer\n",
+            "  Downloading premailer-3.10.0-py2.py3-none-any.whl (19 kB)\n",
+            "Collecting PyMuPDF==1.19.0\n",
+            "  Downloading PyMuPDF-1.19.0-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (8.7 MB)\n",
+            "\u001b[K     |████████████████████████████████| 8.7 MB 19.5 MB/s \n",
+            "\u001b[?25hCollecting lanms-neo==1.0.2\n",
+            "  Downloading lanms_neo-1.0.2.tar.gz (39 kB)\n",
+            "  Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
+            "  Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n",
+            "    Preparing wheel metadata ... \u001b[?25l\u001b[?25hdone\n",
+            "Requirement already satisfied: lxml in /usr/local/lib/python3.7/dist-packages (from paddleocr>=2.0.1) (4.9.1)\n",
+            "Collecting pyclipper\n",
+            "  Downloading pyclipper-1.3.0.post4-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.whl (604 kB)\n",
+            "\u001b[K     |████████████████████████████████| 604 kB 62.9 MB/s \n",
+            "\u001b[?25hRequirement already satisfied: scikit-image in /usr/local/lib/python3.7/dist-packages (from paddleocr>=2.0.1) (0.18.3)\n",
+            "Requirement already satisfied: numpy in /usr/local/lib/python3.7/dist-packages (from paddleocr>=2.0.1) (1.21.6)\n",
+            "Requirement already satisfied: cython in /usr/local/lib/python3.7/dist-packages (from paddleocr>=2.0.1) (0.29.32)\n",
+            "Collecting fire>=0.3.0\n",
+            "  Downloading fire-0.4.0.tar.gz (87 kB)\n",
+            "\u001b[K     |████████████████████████████████| 87 kB 7.9 MB/s \n",
+            "\u001b[?25hRequirement already satisfied: opencv-contrib-python in /usr/local/lib/python3.7/dist-packages (from paddleocr>=2.0.1) (4.6.0.66)\n",
+            "Requirement already satisfied: opencv-python in /usr/local/lib/python3.7/dist-packages (from paddleocr>=2.0.1) (4.6.0.66)\n",
+            "Requirement already satisfied: openpyxl in /usr/local/lib/python3.7/dist-packages (from paddleocr>=2.0.1) (3.0.10)\n",
+            "Collecting rapidfuzz\n",
+            "  Downloading rapidfuzz-2.13.2-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.2 MB)\n",
+            "\u001b[K     |████████████████████████████████| 2.2 MB 52.5 MB/s \n",
+            "\u001b[?25hCollecting pdf2docx\n",
+            "  Downloading pdf2docx-0.5.6-py3-none-any.whl (148 kB)\n",
+            "\u001b[K     |████████████████████████████████| 148 kB 68.2 MB/s \n",
+            "\u001b[?25hRequirement already satisfied: beautifulsoup4 in /usr/local/lib/python3.7/dist-packages (from paddleocr>=2.0.1) (4.6.3)\n",
+            "Collecting attrdict\n",
+            "  Downloading attrdict-2.0.1-py2.py3-none-any.whl (9.9 kB)\n",
+            "Collecting visualdl\n",
+            "  Downloading visualdl-2.4.1-py3-none-any.whl (4.9 MB)\n",
+            "\u001b[K     |████████████████████████████████| 4.9 MB 46.1 MB/s \n",
+            "\u001b[?25hCollecting fonttools>=4.24.0\n",
+            "  Downloading fonttools-4.38.0-py3-none-any.whl (965 kB)\n",
+            "\u001b[K     |████████████████████████████████| 965 kB 57.7 MB/s \n",
+            "\u001b[?25hCollecting Polygon3\n",
+            "  Downloading Polygon3-3.0.9.1.tar.gz (39 kB)\n",
+            "Requirement already satisfied: shapely in /usr/local/lib/python3.7/dist-packages (from paddleocr>=2.0.1) (1.8.5.post1)\n",
+            "Requirement already satisfied: imgaug in /usr/local/lib/python3.7/dist-packages (from paddleocr>=2.0.1) (0.4.0)\n",
+            "Requirement already satisfied: six in /usr/local/lib/python3.7/dist-packages (from fire>=0.3.0->paddleocr>=2.0.1) (1.15.0)\n",
+            "Requirement already satisfied: termcolor in /usr/local/lib/python3.7/dist-packages (from fire>=0.3.0->paddleocr>=2.0.1) (2.1.0)\n",
+            "Requirement already satisfied: scipy in /usr/local/lib/python3.7/dist-packages (from imgaug->paddleocr>=2.0.1) (1.7.3)\n",
+            "Requirement already satisfied: matplotlib in /usr/local/lib/python3.7/dist-packages (from imgaug->paddleocr>=2.0.1) (3.2.2)\n",
+            "Requirement already satisfied: imageio in /usr/local/lib/python3.7/dist-packages (from imgaug->paddleocr>=2.0.1) (2.9.0)\n",
+            "Requirement already satisfied: Pillow in /usr/local/lib/python3.7/dist-packages (from imgaug->paddleocr>=2.0.1) (7.1.2)\n",
+            "Requirement already satisfied: tifffile>=2019.7.26 in /usr/local/lib/python3.7/dist-packages (from scikit-image->paddleocr>=2.0.1) (2021.11.2)\n",
+            "Requirement already satisfied: PyWavelets>=1.1.1 in /usr/local/lib/python3.7/dist-packages (from scikit-image->paddleocr>=2.0.1) (1.3.0)\n",
+            "Requirement already satisfied: networkx>=2.0 in /usr/local/lib/python3.7/dist-packages (from scikit-image->paddleocr>=2.0.1) (2.6.3)\n",
+            "Requirement already satisfied: python-dateutil>=2.1 in /usr/local/lib/python3.7/dist-packages (from matplotlib->imgaug->paddleocr>=2.0.1) (2.8.2)\n",
+            "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.7/dist-packages (from matplotlib->imgaug->paddleocr>=2.0.1) (0.11.0)\n",
+            "Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.7/dist-packages (from matplotlib->imgaug->paddleocr>=2.0.1) (1.4.4)\n",
+            "Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 in /usr/local/lib/python3.7/dist-packages (from matplotlib->imgaug->paddleocr>=2.0.1) (3.0.9)\n",
+            "Requirement already satisfied: typing-extensions in /usr/local/lib/python3.7/dist-packages (from kiwisolver>=1.0.1->matplotlib->imgaug->paddleocr>=2.0.1) (4.1.1)\n",
+            "Requirement already satisfied: et-xmlfile in /usr/local/lib/python3.7/dist-packages (from openpyxl->paddleocr>=2.0.1) (1.1.0)\n",
+            "Collecting cssutils\n",
+            "  Downloading cssutils-2.6.0-py3-none-any.whl (399 kB)\n",
+            "\u001b[K     |████████████████████████████████| 399 kB 56.6 MB/s \n",
+            "\u001b[?25hRequirement already satisfied: cachetools in /usr/local/lib/python3.7/dist-packages (from premailer->paddleocr>=2.0.1) (5.2.0)\n",
+            "Collecting cssselect\n",
+            "  Downloading cssselect-1.2.0-py2.py3-none-any.whl (18 kB)\n",
+            "Requirement already satisfied: requests in /usr/local/lib/python3.7/dist-packages (from premailer->paddleocr>=2.0.1) (2.23.0)\n",
+            "Requirement already satisfied: importlib-metadata in /usr/local/lib/python3.7/dist-packages (from cssutils->premailer->paddleocr>=2.0.1) (4.13.0)\n",
+            "Requirement already satisfied: zipp>=0.5 in /usr/local/lib/python3.7/dist-packages (from importlib-metadata->cssutils->premailer->paddleocr>=2.0.1) (3.10.0)\n",
+            "Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests->premailer->paddleocr>=2.0.1) (1.24.3)\n",
+            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests->premailer->paddleocr>=2.0.1) (2022.9.24)\n",
+            "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests->premailer->paddleocr>=2.0.1) (2.10)\n",
+            "Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests->premailer->paddleocr>=2.0.1) (3.0.4)\n",
+            "Requirement already satisfied: packaging in /usr/local/lib/python3.7/dist-packages (from visualdl->paddleocr>=2.0.1) (21.3)\n",
+            "Collecting Flask-Babel>=1.0.0\n",
+            "  Downloading Flask_Babel-2.0.0-py3-none-any.whl (9.3 kB)\n",
+            "Collecting multiprocess\n",
+            "  Downloading multiprocess-0.70.14-py37-none-any.whl (115 kB)\n",
+            "\u001b[K     |████████████████████████████████| 115 kB 70.8 MB/s \n",
+            "\u001b[?25hRequirement already satisfied: protobuf>=3.11.0 in /usr/local/lib/python3.7/dist-packages (from visualdl->paddleocr>=2.0.1) (3.19.6)\n",
+            "Collecting bce-python-sdk\n",
+            "  Downloading bce_python_sdk-0.8.74-py3-none-any.whl (204 kB)\n",
+            "\u001b[K     |████████████████████████████████| 204 kB 74.4 MB/s \n",
+            "\u001b[?25hRequirement already satisfied: pandas in /usr/local/lib/python3.7/dist-packages (from visualdl->paddleocr>=2.0.1) (1.3.5)\n",
+            "Requirement already satisfied: flask>=1.1.1 in /usr/local/lib/python3.7/dist-packages (from visualdl->paddleocr>=2.0.1) (1.1.4)\n",
+            "Requirement already satisfied: Jinja2<3.0,>=2.10.1 in /usr/local/lib/python3.7/dist-packages (from flask>=1.1.1->visualdl->paddleocr>=2.0.1) (2.11.3)\n",
+            "Requirement already satisfied: itsdangerous<2.0,>=0.24 in /usr/local/lib/python3.7/dist-packages (from flask>=1.1.1->visualdl->paddleocr>=2.0.1) (1.1.0)\n",
+            "Requirement already satisfied: click<8.0,>=5.1 in /usr/local/lib/python3.7/dist-packages (from flask>=1.1.1->visualdl->paddleocr>=2.0.1) (7.1.2)\n",
+            "Requirement already satisfied: Werkzeug<2.0,>=0.15 in /usr/local/lib/python3.7/dist-packages (from flask>=1.1.1->visualdl->paddleocr>=2.0.1) (1.0.1)\n",
+            "Requirement already satisfied: Babel>=2.3 in /usr/local/lib/python3.7/dist-packages (from Flask-Babel>=1.0.0->visualdl->paddleocr>=2.0.1) (2.11.0)\n",
+            "Requirement already satisfied: pytz in /usr/local/lib/python3.7/dist-packages (from Flask-Babel>=1.0.0->visualdl->paddleocr>=2.0.1) (2022.6)\n",
+            "Requirement already satisfied: MarkupSafe>=0.23 in /usr/local/lib/python3.7/dist-packages (from Jinja2<3.0,>=2.10.1->flask>=1.1.1->visualdl->paddleocr>=2.0.1) (2.0.1)\n",
+            "Requirement already satisfied: future>=0.6.0 in /usr/local/lib/python3.7/dist-packages (from bce-python-sdk->visualdl->paddleocr>=2.0.1) (0.16.0)\n",
+            "Collecting pycryptodome>=3.8.0\n",
+            "  Downloading pycryptodome-3.15.0-cp35-abi3-manylinux2010_x86_64.whl (2.3 MB)\n",
+            "\u001b[K     |████████████████████████████████| 2.3 MB 52.8 MB/s \n",
+            "\u001b[?25hRequirement already satisfied: dill>=0.3.6 in /usr/local/lib/python3.7/dist-packages (from multiprocess->visualdl->paddleocr>=2.0.1) (0.3.6)\n",
+            "Building wheels for collected packages: lanms-neo, fire, python-docx, Polygon3\n",
+            "  Building wheel for lanms-neo (PEP 517) ... \u001b[?25l\u001b[?25hdone\n",
+            "  Created wheel for lanms-neo: filename=lanms_neo-1.0.2-cp37-cp37m-linux_x86_64.whl size=110709 sha256=db3be5b526b39f2cdb111fae9919810e45d809fbf6483beb4aef28c3577351e1\n",
+            "  Stored in directory: /root/.cache/pip/wheels/09/7b/5e/1e4d24a8f94c1116afa284ce2968ef2f72b986a5457164b340\n",
+            "  Building wheel for fire (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
+            "  Created wheel for fire: filename=fire-0.4.0-py2.py3-none-any.whl size=115940 sha256=6a35e11384be4e128e9cc6c57ba0a7d5a6dd93ab81674fe4d179f29373f6016e\n",
+            "  Stored in directory: /root/.cache/pip/wheels/8a/67/fb/2e8a12fa16661b9d5af1f654bd199366799740a85c64981226\n",
+            "  Building wheel for python-docx (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
+            "  Created wheel for python-docx: filename=python_docx-0.8.11-py3-none-any.whl size=184508 sha256=39fd6da47445e3f73ed3453c6f584faecf60afde06c3276603ebda99353988d8\n",
+            "  Stored in directory: /root/.cache/pip/wheels/f6/6f/b9/d798122a8b55b74ad30b5f52b01482169b445fbb84a11797a6\n",
+            "  Building wheel for Polygon3 (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
+            "  Created wheel for Polygon3: filename=Polygon3-3.0.9.1-cp37-cp37m-linux_x86_64.whl size=102659 sha256=41f609300d5ade5b91d4f4b3bd34ac510e7b2ccfbf1ebd338f17d917ab63cd02\n",
+            "  Stored in directory: /root/.cache/pip/wheels/0d/f3/a1/d9909fbad83c438786f3fbde79b0636c9e843107bad74baba7\n",
+            "Successfully built lanms-neo fire python-docx Polygon3\n",
+            "Installing collected packages: pycryptodome, python-docx, PyMuPDF, multiprocess, fonttools, Flask-Babel, fire, cssutils, cssselect, bce-python-sdk, visualdl, rapidfuzz, pyclipper, premailer, Polygon3, pdf2docx, lanms-neo, attrdict, paddleocr\n",
+            "Successfully installed Flask-Babel-2.0.0 Polygon3-3.0.9.1 PyMuPDF-1.19.0 attrdict-2.0.1 bce-python-sdk-0.8.74 cssselect-1.2.0 cssutils-2.6.0 fire-0.4.0 fonttools-4.38.0 lanms-neo-1.0.2 multiprocess-0.70.14 paddleocr-2.6.1.0 pdf2docx-0.5.6 premailer-3.10.0 pyclipper-1.3.0.post4 pycryptodome-3.15.0 python-docx-0.8.11 rapidfuzz-2.13.2 visualdl-2.4.1\n",
+            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
+            "Collecting protobuf==3.20.0\n",
+            "  Downloading protobuf-3.20.0-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.whl (1.0 MB)\n",
+            "\u001b[K     |████████████████████████████████| 1.0 MB 8.3 MB/s \n",
+            "\u001b[?25hInstalling collected packages: protobuf\n",
+            "  Attempting uninstall: protobuf\n",
+            "    Found existing installation: protobuf 3.19.6\n",
+            "    Uninstalling protobuf-3.19.6:\n",
+            "      Successfully uninstalled protobuf-3.19.6\n",
+            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
+            "tensorflow 2.9.2 requires protobuf<3.20,>=3.9.2, but you have protobuf 3.20.0 which is incompatible.\n",
+            "tensorboard 2.9.1 requires protobuf<3.20,>=3.9.2, but you have protobuf 3.20.0 which is incompatible.\n",
+            "google-cloud-translate 3.8.4 requires protobuf!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.19.5, but you have protobuf 3.20.0 which is incompatible.\n",
+            "google-cloud-language 2.6.1 requires protobuf!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.19.5, but you have protobuf 3.20.0 which is incompatible.\n",
+            "google-cloud-firestore 2.7.2 requires protobuf!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.19.5, but you have protobuf 3.20.0 which is incompatible.\n",
+            "google-cloud-datastore 2.9.0 requires protobuf!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.19.5, but you have protobuf 3.20.0 which is incompatible.\n",
+            "google-cloud-bigquery 3.3.6 requires protobuf!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.19.5, but you have protobuf 3.20.0 which is incompatible.\n",
+            "google-cloud-bigquery-storage 2.16.2 requires protobuf!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.19.5, but you have protobuf 3.20.0 which is incompatible.\u001b[0m\n",
+            "Successfully installed protobuf-3.20.0\n"
+          ]
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "application/vnd.colab-display-data+json": {
+              "pip_warning": {
+                "packages": [
+                  "google"
+                ]
+              }
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Cloning into 'PaddleOCR'...\n",
+            "remote: Enumerating objects: 44967, done.\u001b[K\n",
+            "remote: Counting objects: 100% (98/98), done.\u001b[K\n",
+            "remote: Compressing objects: 100% (75/75), done.\u001b[K\n",
+            "remote: Total 44967 (delta 43), reused 45 (delta 23), pack-reused 44869\u001b[K\n",
+            "Receiving objects: 100% (44967/44967), 338.24 MiB | 33.36 MiB/s, done.\n",
+            "Resolving deltas: 100% (31741/31741), done.\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "a=5"
+      ],
+      "metadata": {
+        "id": "IXEKTAa2_10K"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "!wget https://paddleocr.bj.bcebos.com/whl/layoutparser-0.0.0-py3-none-any.whl\n",
+        "!pip install -U layoutparser-0.0.0-py3-none-any.whl"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "8gWFgGl5CXu6",
+        "outputId": "5d435097-2f57-4806-f454-eeeeb1a02efc"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "--2022-11-18 12:58:08--  https://paddleocr.bj.bcebos.com/whl/layoutparser-0.0.0-py3-none-any.whl\n",
+            "Resolving paddleocr.bj.bcebos.com (paddleocr.bj.bcebos.com)... 103.235.46.61, 2409:8c04:1001:1002:0:ff:b001:368a\n",
+            "Connecting to paddleocr.bj.bcebos.com (paddleocr.bj.bcebos.com)|103.235.46.61|:443... connected.\n",
+            "HTTP request sent, awaiting response... 200 OK\n",
+            "Length: 19145360 (18M) [application/octet-stream]\n",
+            "Saving to: ‘layoutparser-0.0.0-py3-none-any.whl’\n",
+            "\n",
+            "layoutparser-0.0.0- 100%[===================>]  18.26M  3.69MB/s    in 12s     \n",
+            "\n",
+            "2022-11-18 12:58:23 (1.48 MB/s) - ‘layoutparser-0.0.0-py3-none-any.whl’ saved [19145360/19145360]\n",
+            "\n",
+            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
+            "Processing ./layoutparser-0.0.0-py3-none-any.whl\n",
+            "Requirement already satisfied: numpy in /usr/local/lib/python3.7/dist-packages (from layoutparser==0.0.0) (1.21.6)\n",
+            "Requirement already satisfied: pandas in /usr/local/lib/python3.7/dist-packages (from layoutparser==0.0.0) (1.3.5)\n",
+            "Requirement already satisfied: tqdm in /usr/local/lib/python3.7/dist-packages (from layoutparser==0.0.0) (4.64.1)\n",
+            "Collecting iopath\n",
+            "  Downloading iopath-0.1.10.tar.gz (42 kB)\n",
+            "\u001b[K     |████████████████████████████████| 42 kB 38 kB/s \n",
+            "\u001b[?25hRequirement already satisfied: pillow in /usr/local/lib/python3.7/dist-packages (from layoutparser==0.0.0) (7.1.2)\n",
+            "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.7/dist-packages (from layoutparser==0.0.0) (6.0)\n",
+            "Requirement already satisfied: opencv-python in /usr/local/lib/python3.7/dist-packages (from layoutparser==0.0.0) (4.6.0.66)\n",
+            "Requirement already satisfied: typing_extensions in /usr/local/lib/python3.7/dist-packages (from iopath->layoutparser==0.0.0) (4.1.1)\n",
+            "Collecting portalocker\n",
+            "  Downloading portalocker-2.6.0-py2.py3-none-any.whl (15 kB)\n",
+            "Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.7/dist-packages (from pandas->layoutparser==0.0.0) (2022.6)\n",
+            "Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.7/dist-packages (from pandas->layoutparser==0.0.0) (2.8.2)\n",
+            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.7/dist-packages (from python-dateutil>=2.7.3->pandas->layoutparser==0.0.0) (1.15.0)\n",
+            "Building wheels for collected packages: iopath\n",
+            "  Building wheel for iopath (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
+            "  Created wheel for iopath: filename=iopath-0.1.10-py3-none-any.whl size=31548 sha256=8f3da2a0ce4dd2c6b432ef4d5851d960b4c889e015e7066a5a77b45bfa05cb60\n",
+            "  Stored in directory: /root/.cache/pip/wheels/aa/cc/ed/ca4e88beef656b01c84b9185196513ef2faf74a5a379b043a7\n",
+            "Successfully built iopath\n",
+            "Installing collected packages: portalocker, iopath, layoutparser\n",
+            "Successfully installed iopath-0.1.10 layoutparser-0.0.0 portalocker-2.6.0\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "## Table Extraction"
+      ],
+      "metadata": {
+        "id": "w5MA08E0F8aU"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "import cv2\n",
+        "import layoutparser as lp\n",
+        "image = cv2.imread(\"/content/pages/page13.jpg\")\n",
+        "\n",
+        "image = image[..., ::-1]\n",
+        "\n",
+        "# load model\n",
+        "model = lp.PaddleDetectionLayoutModel(config_path=\"lp://PubLayNet/ppyolov2_r50vd_dcn_365e_publaynet/config\",\n",
+        "                                threshold=0.5,\n",
+        "                                label_map={0: \"Text\", 1: \"Title\", 2: \"List\", 3:\"Table\", 4:\"Figure\"},\n",
+        "                                enforce_cpu=False,\n",
+        "                                enable_mkldnn=True)#math kernel library\n",
+        "# detect\n",
+        "layout = model.detect(image)"
+      ],
+      "metadata": {
+        "id": "bw9SFYnMCX0E",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "89218fbd-3b01-453e-a191-0d15c8883d03"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "download https://paddle-model-ecology.bj.bcebos.com/model/layout-parser/ppyolov2_r50vd_dcn_365e_publaynet.tar to /root/.paddledet/inference_model/ppyolov2_r50vd_dcn_365e_publaynet/ppyolov2_r50vd_dcn_365e_publaynet_infer/ppyolov2_r50vd_dcn_365e_publaynet.tar\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "100%|██████████| 221M/221M [00:37<00:00, 5.92MiB/s]\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "layout"
+      ],
+      "metadata": {
+        "id": "G76oO2WXCX6v",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "2b0f9ed6-ff8c-4b46-b69c-5e3961d017d4"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "Layout(_blocks=[TextBlock(block=Rectangle(x_1=300.35406494140625, y_1=1716.4278564453125, x_2=1401.105712890625, y_2=1876.4561767578125), text=None, id=None, type=Text, parent=None, next=None, score=0.947794497013092), TextBlock(block=Rectangle(x_1=296.242431640625, y_1=1969.3675537109375, x_2=1405.8653564453125, y_2=2034.4422607421875), text=None, id=None, type=Text, parent=None, next=None, score=0.934190034866333), TextBlock(block=Rectangle(x_1=296.2332763671875, y_1=1460.10986328125, x_2=1401.1175537109375, y_2=1553.036865234375), text=None, id=None, type=Text, parent=None, next=None, score=0.924132227897644), TextBlock(block=Rectangle(x_1=294.98626708984375, y_1=444.1419677734375, x_2=1408.130126953125, y_2=567.1005249023438), text=None, id=None, type=Text, parent=None, next=None, score=0.9196642637252808), TextBlock(block=Rectangle(x_1=300.4600830078125, y_1=1669.076171875, x_2=711.9566040039062, y_2=1697.28076171875), text=None, id=None, type=Title, parent=None, next=None, score=0.8556817770004272), TextBlock(block=Rectangle(x_1=297.86297607421875, y_1=220.03121948242188, x_2=1409.0029296875, y_2=418.0099182128906), text=None, id=None, type=Table, parent=None, next=None, score=0.7598645091056824), TextBlock(block=Rectangle(x_1=298.9613342285156, y_1=1601.4661865234375, x_2=687.694580078125, y_2=1633.7120361328125), text=None, id=None, type=Title, parent=None, next=None, score=0.7429183125495911), TextBlock(block=Rectangle(x_1=295.4989318847656, y_1=1405.8271484375, x_2=551.2619018554688, y_2=1438.658203125), text=None, id=None, type=Title, parent=None, next=None, score=0.6753251552581787), TextBlock(block=Rectangle(x_1=282.51495361328125, y_1=647.5087890625, x_2=1415.5732421875, y_2=1368.4254150390625), text=None, id=None, type=List, parent=None, next=None, score=0.6743354201316833), TextBlock(block=Rectangle(x_1=298.611328125, y_1=1063.1019287109375, x_2=366.89483642578125, y_2=1092.1378173828125), text=None, id=None, type=Text, parent=None, next=None, score=0.6345258951187134), TextBlock(block=Rectangle(x_1=298.71820068359375, y_1=1171.6640625, x_2=998.8455200195312, y_2=1205.39306640625), text=None, id=None, type=Text, parent=None, next=None, score=0.6338083148002625), TextBlock(block=Rectangle(x_1=294.16180419921875, y_1=931.6088256835938, x_2=1402.220458984375, y_2=996.5545043945312), text=None, id=None, type=Text, parent=None, next=None, score=0.5081444382667542)], page_data={})"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 13
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "x_1=0\n",
+        "y_1=0\n",
+        "x_2=0\n",
+        "y_2=0\n",
+        "\n",
+        "for l in layout:\n",
+        "  #print(l)\n",
+        "  if l.type == 'Table':\n",
+        "    x_1 = int(l.block.x_1)\n",
+        "    print(l.block.x_1)\n",
+        "    y_1 = int(l.block.y_1)\n",
+        "    x_2 = int(l.block.x_2)\n",
+        "    y_2 = int(l.block.y_2)\n",
+        "\n",
+        "    break"
+      ],
+      "metadata": {
+        "id": "y3h0kCz-CX_U",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "5b44d211-694b-409f-df7c-69189d4b448f"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "297.86298\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "print(x_1,y_1,x_2,y_2)"
+      ],
+      "metadata": {
+        "id": "cdiYPeCJCYIg",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "4160ed2b-e1d1-4174-dd2e-55bee31167f3"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "297 220 1409 418\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "im = cv2.imread('/content/pages/page13.jpg')"
+      ],
+      "metadata": {
+        "id": "F39kJV3hCYLV"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "cv2.imwrite('ext_im.jpg', im[y_1:y_2,x_1:x_2])"
+      ],
+      "metadata": {
+        "id": "EQDXSNijCYPs",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "9c0e6954-da96-491b-efcb-318dc5410561"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "True"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 17
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [],
+      "metadata": {
+        "id": "7O2P4aIMor_e"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "EGwGhHnd8i_h"
+      },
+      "source": [
+        "# Text Detection and Recognition"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "from paddleocr import PaddleOCR, draw_ocr"
+      ],
+      "metadata": {
+        "id": "N6WQZXhLLDWk"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "ocr = PaddleOCR(lang='en')\n",
+        "image_path = '/content/ext_im.jpg'\n",
+        "image_cv = cv2.imread(image_path)\n",
+        "image_height = image_cv.shape[0]\n",
+        "image_width = image_cv.shape[1]\n",
+        "output = ocr.ocr(image_path)[0]"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "A8bCZ9AULDZF",
+        "outputId": "78de4243-7a38-4378-8dfd-063004300535"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "download https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_det_infer.tar to /root/.paddleocr/whl/det/en/en_PP-OCRv3_det_infer/en_PP-OCRv3_det_infer.tar\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "100%|██████████| 4.00M/4.00M [00:07<00:00, 505kiB/s] \n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "download https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_rec_infer.tar to /root/.paddleocr/whl/rec/en/en_PP-OCRv3_rec_infer/en_PP-OCRv3_rec_infer.tar\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "100%|██████████| 9.96M/9.96M [00:14<00:00, 693kiB/s] \n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "download https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar to /root/.paddleocr/whl/cls/ch_ppocr_mobile_v2.0_cls_infer/ch_ppocr_mobile_v2.0_cls_infer.tar\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "100%|██████████| 2.19M/2.19M [00:11<00:00, 190kiB/s]"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "[2022/11/18 13:00:00] ppocr DEBUG: Namespace(alpha=1.0, benchmark=False, beta=1.0, cls_batch_num=6, cls_image_shape='3, 48, 192', cls_model_dir='/root/.paddleocr/whl/cls/ch_ppocr_mobile_v2.0_cls_infer', cls_thresh=0.9, cpu_threads=10, crop_res_save_dir='./output', det=True, det_algorithm='DB', det_box_type='quad', det_db_box_thresh=0.6, det_db_score_mode='fast', det_db_thresh=0.3, det_db_unclip_ratio=1.5, det_east_cover_thresh=0.1, det_east_nms_thresh=0.2, det_east_score_thresh=0.8, det_limit_side_len=960, det_limit_type='max', det_model_dir='/root/.paddleocr/whl/det/en/en_PP-OCRv3_det_infer', det_pse_box_thresh=0.85, det_pse_min_area=16, det_pse_scale=1, det_pse_thresh=0, det_sast_nms_thresh=0.2, det_sast_score_thresh=0.5, draw_img_save_dir='./inference_results', drop_score=0.5, e2e_algorithm='PGNet', e2e_char_dict_path='./ppocr/utils/ic15_dict.txt', e2e_limit_side_len=768, e2e_limit_type='max', e2e_model_dir=None, e2e_pgnet_mode='fast', e2e_pgnet_score_thresh=0.5, e2e_pgnet_valid_set='totaltext', enable_mkldnn=False, fourier_degree=5, gpu_mem=500, help='==SUPPRESS==', image_dir=None, image_orientation=False, ir_optim=True, kie_algorithm='LayoutXLM', label_list=['0', '180'], lang='en', layout=True, layout_dict_path=None, layout_model_dir=None, layout_nms_threshold=0.5, layout_score_threshold=0.5, max_batch_size=10, max_text_length=25, merge_no_span_structure=True, min_subgraph_size=15, mode='structure', ocr=True, ocr_order_method=None, ocr_version='PP-OCRv3', output='./output', page_num=0, precision='fp32', process_id=0, re_model_dir=None, rec=True, rec_algorithm='SVTR_LCNet', rec_batch_num=6, rec_char_dict_path='/usr/local/lib/python3.7/dist-packages/paddleocr/ppocr/utils/en_dict.txt', rec_image_inverse=True, rec_image_shape='3, 48, 320', rec_model_dir='/root/.paddleocr/whl/rec/en/en_PP-OCRv3_rec_infer', recovery=False, save_crop_res=False, save_log_path='./log_output/', scales=[8, 16, 32], ser_dict_path='../train_data/XFUND/class_list_xfun.txt', ser_model_dir=None, show_log=True, sr_batch_num=1, sr_image_shape='3, 32, 128', sr_model_dir=None, structure_version='PP-Structurev2', table=True, table_algorithm='TableAttn', table_char_dict_path=None, table_max_len=488, table_model_dir=None, total_process_num=1, type='ocr', use_angle_cls=False, use_dilation=False, use_gpu=True, use_mp=False, use_npu=False, use_onnx=False, use_pdf2docx_api=False, use_pdserving=False, use_space_char=True, use_tensorrt=False, use_visual_backbone=True, use_xpu=False, vis_font_path='./doc/fonts/simfang.ttf', warmup=False)\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "[2022/11/18 13:00:00] ppocr WARNING: Since the angle classifier is not initialized, the angle classifier will not be uesd during the forward process\n",
+            "[2022/11/18 13:00:01] ppocr DEBUG: dt_boxes num : 42, elapse : 0.12288975715637207\n",
+            "[2022/11/18 13:00:01] ppocr DEBUG: rec_res num  : 42, elapse : 0.12553930282592773\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "print(output)"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "VBIDZA0XLDeA",
+        "outputId": "b86018c1-5b24-4897-9174-a34299909bf7"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "[[[[693.0, 4.0], [755.0, 4.0], [755.0, 36.0], [693.0, 36.0]], ('GPU', 0.9990124106407166)], [[[70.0, 5.0], [148.0, 5.0], [148.0, 36.0], [70.0, 36.0]], ('Model', 0.9997721910476685)], [[[230.0, 5.0], [394.0, 8.0], [394.0, 37.0], [229.0, 35.0]], ('Updates (105)', 0.9652137756347656)], [[[425.0, 5.0], [511.0, 5.0], [511.0, 36.0], [425.0, 36.0]], ('Epochs', 0.9998965263366699)], [[[537.0, 5.0], [612.0, 5.0], [612.0, 36.0], [537.0, 36.0]], ('Hours', 0.9620624780654907)], [[[833.0, 4.0], [958.0, 4.0], [958.0, 33.0], [833.0, 33.0]], ('Train NLL', 0.9994094371795654)], [[[988.0, 6.0], [1104.0, 6.0], [1104.0, 32.0], [988.0, 32.0]], ('Dev.NLL', 0.9872051477432251)], [[[42.0, 47.0], [177.0, 47.0], [177.0, 72.0], [42.0, 72.0]], ('RNNenc-30', 0.9995856881141663)], [[[285.0, 46.0], [341.0, 46.0], [341.0, 74.0], [285.0, 74.0]], ('8.46', 0.9999933242797852)], [[[446.0, 46.0], [489.0, 46.0], [489.0, 74.0], [446.0, 74.0]], ('6.4', 0.9964627623558044)], [[[553.0, 45.0], [599.0, 45.0], [599.0, 74.0], [553.0, 74.0]], ('109', 0.9999635815620422)], [[[641.0, 47.0], [805.0, 47.0], [805.0, 72.0], [641.0, 72.0]], ('TITAN BLACK', 0.9913126230239868)], [[[869.0, 43.0], [923.0, 43.0], [923.0, 75.0], [869.0, 75.0]], ('28.1', 0.999950110912323)], [[[1019.0, 46.0], [1075.0, 46.0], [1075.0, 74.0], [1019.0, 74.0]], ('53.0', 0.999934196472168)], [[[41.0, 75.0], [177.0, 75.0], [177.0, 101.0], [41.0, 101.0]], ('RNNenc-50', 0.9980602264404297)], [[[285.0, 75.0], [341.0, 75.0], [341.0, 104.0], [285.0, 104.0]], ('6.00', 0.9998406171798706)], [[[446.0, 74.0], [489.0, 74.0], [489.0, 104.0], [446.0, 104.0]], ('4.5', 0.9982914924621582)], [[[553.0, 74.0], [599.0, 74.0], [599.0, 104.0], [553.0, 104.0]], ('108', 0.9998137950897217)], [[[644.0, 78.0], [804.0, 78.0], [804.0, 103.0], [644.0, 103.0]], ('Quadro K-6000', 0.9990899562835693)], [[[868.0, 73.0], [927.0, 73.0], [927.0, 105.0], [868.0, 105.0]], ('44.0', 0.999671459197998)], [[[1017.0, 73.0], [1076.0, 73.0], [1076.0, 105.0], [1017.0, 105.0]], ('43.6', 0.9998911619186401)], [[[27.0, 109.0], [193.0, 109.0], [193.0, 134.0], [27.0, 134.0]], ('RNNsearch-30', 0.9990729689598083)], [[[284.0, 108.0], [338.0, 108.0], [338.0, 136.0], [284.0, 136.0]], ('4.71', 0.9994158744812012)], [[[445.0, 108.0], [489.0, 108.0], [489.0, 136.0], [445.0, 136.0]], ('3.6', 0.9944102168083191)], [[[553.0, 108.0], [599.0, 108.0], [599.0, 136.0], [553.0, 136.0]], ('113', 0.9994351267814636)], [[[643.0, 111.0], [804.0, 111.0], [804.0, 132.0], [643.0, 132.0]], ('TITAN BLACK', 0.9635356664657593)], [[[870.0, 108.0], [923.0, 108.0], [923.0, 136.0], [870.0, 136.0]], ('26.7', 0.9992948770523071)], [[[1018.0, 108.0], [1074.0, 108.0], [1074.0, 136.0], [1018.0, 136.0]], ('47.2', 0.9993252158164978)], [[[25.0, 139.0], [193.0, 139.0], [193.0, 163.0], [25.0, 163.0]], ('RNNsearch-50', 0.9973625540733337)], [[[285.0, 137.0], [339.0, 137.0], [339.0, 166.0], [285.0, 166.0]], ('2.88', 0.9999485015869141)], [[[445.0, 134.0], [489.0, 134.0], [489.0, 168.0], [445.0, 168.0]], ('2.2', 0.9979038238525391)], [[[551.0, 137.0], [598.0, 137.0], [598.0, 166.0], [551.0, 166.0]], ('111', 0.9987512230873108)], [[[643.0, 140.0], [804.0, 140.0], [804.0, 165.0], [643.0, 165.0]], ('Quadro K-6000', 0.9971157908439636)], [[[870.0, 137.0], [924.0, 137.0], [924.0, 166.0], [870.0, 166.0]], ('40.7', 0.9991925954818726)], [[[1018.0, 135.0], [1075.0, 135.0], [1075.0, 167.0], [1018.0, 167.0]], ('38.1', 0.9999594688415527)], [[[21.0, 172.0], [196.0, 172.0], [196.0, 193.0], [21.0, 193.0]], ('RNNsearch-50*', 0.9954861402511597)], [[[285.0, 170.0], [338.0, 170.0], [338.0, 197.0], [285.0, 197.0]], ('6.67', 0.9998753666877747)], [[[446.0, 170.0], [489.0, 170.0], [489.0, 197.0], [446.0, 197.0]], ('5.0', 0.9963653683662415)], [[[551.0, 170.0], [600.0, 170.0], [600.0, 197.0], [551.0, 197.0]], ('252', 0.9991322159767151)], [[[644.0, 172.0], [804.0, 172.0], [804.0, 197.0], [644.0, 197.0]], ('Quadro K-6000', 0.9994592666625977)], [[[870.0, 170.0], [923.0, 170.0], [923.0, 197.0], [870.0, 197.0]], ('36.7', 0.9990472793579102)], [[[1019.0, 170.0], [1074.0, 170.0], [1074.0, 197.0], [1019.0, 197.0]], ('35.2', 0.9986913204193115)]]\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "boxes = [line[0] for line in output]\n",
+        "texts = [line[1][0] for line in output]\n",
+        "probabilities = [line[1][1] for line in output]"
+      ],
+      "metadata": {
+        "id": "nNMBAQ78LDgG"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "image_boxes = image_cv.copy()\n"
+      ],
+      "metadata": {
+        "id": "uukcg4SWV_dg"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "for box,text in zip(boxes,texts):\n",
+        "  cv2.rectangle(image_boxes, (int(box[0][0]),int(box[0][1])), (int(box[2][0]),int(box[2][1])),(0,0,255),1)\n",
+        "  cv2.putText(image_boxes, text,(int(box[0][0]),int(box[0][1])),cv2.FONT_HERSHEY_SIMPLEX,1,(222,0,0),1)"
+      ],
+      "metadata": {
+        "id": "l_HzbiA7V_fw"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "cv2.imwrite('detections.jpg', image_boxes)"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "PfUG9mcgV_iJ",
+        "outputId": "b97aaa44-61b9-4a62-dd01-c8c26b66e9c7"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "True"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 24
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "kYWt0lzDHZNp"
+      },
+      "source": [
+        "# Reconstruction"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "## Get Horizontal and Vertical Lines"
+      ],
+      "metadata": {
+        "id": "ruzifYJz4H6y"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "im = image_cv.copy()"
+      ],
+      "metadata": {
+        "id": "YLIoKedcqby_"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "horiz_boxes = []\n",
+        "vert_boxes = []\n",
+        "\n",
+        "for box in boxes:\n",
+        "  x_h, x_v = 0,int(box[0][0])\n",
+        "  y_h, y_v = int(box[0][1]),0\n",
+        "  width_h,width_v = image_width, int(box[2][0]-box[0][0])\n",
+        "  height_h,height_v = int(box[2][1]-box[0][1]),image_height\n",
+        "\n",
+        "  horiz_boxes.append([x_h,y_h,x_h+width_h,y_h+height_h])\n",
+        "  vert_boxes.append([x_v,y_v,x_v+width_v,y_v+height_v])\n",
+        "\n",
+        "  cv2.rectangle(im,(x_h,y_h), (x_h+width_h,y_h+height_h),(0,0,255),1)\n",
+        "  cv2.rectangle(im,(x_v,y_v), (x_v+width_v,y_v+height_v),(0,255,0),1)\n",
+        ""
+      ],
+      "metadata": {
+        "id": "GwcAAe-wccnF"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "cv2.imwrite('horiz_vert.jpg',im)"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "7UxFGhMkccph",
+        "outputId": "344b62aa-8bbf-46e0-ccea-bd1c5eb60e3a"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "True"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 27
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "## Non-Max Suppression"
+      ],
+      "metadata": {
+        "id": "ekVFvJrM4ROL"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "horiz_out = tf.image.non_max_suppression(\n",
+        "    horiz_boxes,\n",
+        "    probabilities,\n",
+        "    max_output_size = 1000,\n",
+        "    iou_threshold=0.1,\n",
+        "    score_threshold=float('-inf'),\n",
+        "    name=None\n",
+        ")"
+      ],
+      "metadata": {
+        "id": "4LVSSB2fcoe7"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "horiz_lines = np.sort(np.array(horiz_out))\n",
+        "print(horiz_lines)"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "pOboYpGnccr2",
+        "outputId": "02933914-32bb-4b3d-88bb-72745b6dda8b"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "[ 3  8 20 24 34 36]\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "im_nms = image_cv.copy()"
+      ],
+      "metadata": {
+        "id": "pfxHrn3iccyK"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "for val in horiz_lines:\n",
+        "  cv2.rectangle(im_nms, (int(horiz_boxes[val][0]),int(horiz_boxes[val][1])), (int(horiz_boxes[val][2]),int(horiz_boxes[val][3])),(0,0,255),1)\n",
+        ""
+      ],
+      "metadata": {
+        "id": "68PCHfmZcc0L"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "cv2.imwrite('im_nms.jpg',im_nms)"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "Z8r9qpiAcc2X",
+        "outputId": "9510d3cf-3870-4c77-b9ff-dd903f9a7902"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "True"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 32
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "vert_out = tf.image.non_max_suppression(\n",
+        "    vert_boxes,\n",
+        "    probabilities,\n",
+        "    max_output_size = 1000,\n",
+        "    iou_threshold=0.1,\n",
+        "    score_threshold=float('-inf'),\n",
+        "    name=None\n",
+        ")"
+      ],
+      "metadata": {
+        "id": "mKgPuh7rcc4s"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "print(vert_out)"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "GBpKsImVcc6p",
+        "outputId": "f7bfbf04-9318-4230-f9df-98101fc7cadd"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "tf.Tensor([ 8 10 34 12  3  1 39], shape=(7,), dtype=int32)\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "vert_lines = np.sort(np.array(vert_out))\n",
+        "print(vert_lines)"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "K0lBh-yz5YLp",
+        "outputId": "31a4ea8a-27ce-4b53-9bdb-9857c65ebdaa"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "[ 1  3  8 10 12 34 39]\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "for val in vert_lines:\n",
+        "  cv2.rectangle(im_nms, (int(vert_boxes[val][0]),int(vert_boxes[val][1])), (int(vert_boxes[val][2]),int(vert_boxes[val][3])),(255,0,0),1)\n",
+        ""
+      ],
+      "metadata": {
+        "id": "WqsLm0L_cc84"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "cv2.imwrite('im_nms.jpg',im_nms)"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "xZOEa7lpcdGM",
+        "outputId": "a92cbce5-7529-4b3b-f4b5-2c016904ab21"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "True"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 37
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "## Convert to CSV"
+      ],
+      "metadata": {
+        "id": "116eBUrO93-i"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "\n",
+        "\n",
+        "out_array = [[\"\" for i in range(len(vert_lines))] for j in range(len(horiz_lines))]\n",
+        "print(np.array(out_array).shape)\n",
+        "print(out_array)"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "HRQzwVUTcdIq",
+        "outputId": "93b6914b-c713-48e0-ecaf-87a764a48d13"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "(6, 7)\n",
+            "[['', '', '', '', '', '', ''], ['', '', '', '', '', '', ''], ['', '', '', '', '', '', ''], ['', '', '', '', '', '', ''], ['', '', '', '', '', '', ''], ['', '', '', '', '', '', '']]\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "\n",
+        "unordered_boxes = []\n",
+        "\n",
+        "for i in vert_lines:\n",
+        "  print(vert_boxes[i])\n",
+        "  unordered_boxes.append(vert_boxes[i][0])"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "sSrupaRZIAk_",
+        "outputId": "61055c32-2de2-4a31-c36f-e3857a6cc939"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "[70, 0, 148, 198]\n",
+            "[425, 0, 511, 198]\n",
+            "[285, 0, 341, 198]\n",
+            "[553, 0, 599, 198]\n",
+            "[869, 0, 923, 198]\n",
+            "[1018, 0, 1075, 198]\n",
+            "[644, 0, 804, 198]\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "ordered_boxes = np.argsort(unordered_boxes)\n",
+        "print(ordered_boxes)"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "lRMlVNh_HuJV",
+        "outputId": "de3751a5-525d-4659-acbc-00d61fcbeba1"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "[0 2 1 3 6 4 5]\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "def intersection(box_1, box_2):\n",
+        "  return [box_2[0], box_1[1],box_2[2], box_1[3]]"
+      ],
+      "metadata": {
+        "id": "AHHaxKUuC6jQ"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "def iou(box_1, box_2):\n",
+        "\n",
+        "  x_1 = max(box_1[0], box_2[0])\n",
+        "  y_1 = max(box_1[1], box_2[1])\n",
+        "  x_2 = min(box_1[2], box_2[2])\n",
+        "  y_2 = min(box_1[3], box_2[3])\n",
+        "\n",
+        "  inter = abs(max((x_2 - x_1, 0)) * max((y_2 - y_1), 0))\n",
+        "  if inter == 0:\n",
+        "      return 0\n",
+        "\n",
+        "  box_1_area = abs((box_1[2] - box_1[0]) * (box_1[3] - box_1[1]))\n",
+        "  box_2_area = abs((box_2[2] - box_2[0]) * (box_2[3] - box_2[1]))\n",
+        "\n",
+        "  return inter / float(box_1_area + box_2_area - inter)"
+      ],
+      "metadata": {
+        "id": "fDVb0DkxJSIf"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "for i in range(len(horiz_lines)):\n",
+        "  for j in range(len(vert_lines)):\n",
+        "    resultant = intersection(horiz_boxes[horiz_lines[i]], vert_boxes[vert_lines[ordered_boxes[j]]] )\n",
+        "\n",
+        "    for b in range(len(boxes)):\n",
+        "      the_box = [boxes[b][0][0],boxes[b][0][1],boxes[b][2][0],boxes[b][2][1]]\n",
+        "      if(iou(resultant,the_box)>0.1):\n",
+        "        out_array[i][j] = texts[b]"
+      ],
+      "metadata": {
+        "id": "LWGhCwg6BIoL"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "out_array=np.array(out_array)"
+      ],
+      "metadata": {
+        "id": "c4tEY9LGNIM9"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "out_array"
+      ],
+      "metadata": {
+        "id": "_ekto4-Ymxv2",
+        "outputId": "f7a8e379-2879-4ed0-e8c0-4e127aacc50a",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        }
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "array([['Model', 'Updates (105)', 'Epochs', 'Hours', 'GPU', 'Train NLL',\n",
+              "        'Dev.NLL'],\n",
+              "       ['RNNenc-30', '8.46', '6.4', '109', 'TITAN BLACK', '28.1', '53.0'],\n",
+              "       ['RNNenc-50', '6.00', '4.5', '108', 'Quadro K-6000', '44.0',\n",
+              "        '43.6'],\n",
+              "       ['RNNsearch-30', '4.71', '3.6', '113', 'TITAN BLACK', '26.7',\n",
+              "        '47.2'],\n",
+              "       ['RNNsearch-50', '2.88', '2.2', '111', 'Quadro K-6000', '40.7',\n",
+              "        '38.1'],\n",
+              "       ['RNNsearch-50*', '6.67', '5.0', '252', 'Quadro K-6000', '36.7',\n",
+              "        '35.2']], dtype='<U13')"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 45
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "pd.DataFrame(out_array).to_csv('sample.csv')"
+      ],
+      "metadata": {
+        "id": "D8UdX80wBI9V"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "## Merging Cells"
+      ],
+      "metadata": {
+        "id": "E693Ela3qhLx"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "current_bank=['']*len(out_array[0,:])\n",
+        "print(current_bank)"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "XNcX7fEWPDfw",
+        "outputId": "06cb1313-e8b8-4252-d305-f03fc03d14ed"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "['', '', '', '', '', '', '']\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "def empty(arr):\n",
+        "  for i in arr:\n",
+        "    if i=='':\n",
+        "      return True\n",
+        "  return False"
+      ],
+      "metadata": {
+        "id": "TTF5ojcCQJKR"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "cleaned_array=[]"
+      ],
+      "metadata": {
+        "id": "3w1amnEXSVSB"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "for i in range(len(out_array)):\n",
+        "  if not empty(out_array[i]):\n",
+        "    current_bank=[out_array[i][j] for j in range(len(out_array[i]))]\n",
+        "    cleaned_array.append(current_bank)\n",
+        "    not_empty=True\n",
+        "  else:\n",
+        "    for j in range(len(out_array[i])):\n",
+        "      current_bank[j]+=' '+out_array[i][j]\n",
+        "    print('-->',current_bank)\n",
+        "cleaned_array=np.array(cleaned_array)\n",
+        "print(cleaned_array)"
+      ],
+      "metadata": {
+        "id": "W_q9e2EkPepQ",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "fba25f38-1e56-45c3-88fe-2211d38d4dca"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "[['Model' 'Updates (105)' 'Epochs' 'Hours' 'GPU' 'Train NLL' 'Dev.NLL']\n",
+            " ['RNNenc-30' '8.46' '6.4' '109' 'TITAN BLACK' '28.1' '53.0']\n",
+            " ['RNNenc-50' '6.00' '4.5' '108' 'Quadro K-6000' '44.0' '43.6']\n",
+            " ['RNNsearch-30' '4.71' '3.6' '113' 'TITAN BLACK' '26.7' '47.2']\n",
+            " ['RNNsearch-50' '2.88' '2.2' '111' 'Quadro K-6000' '40.7' '38.1']\n",
+            " ['RNNsearch-50*' '6.67' '5.0' '252' 'Quadro K-6000' '36.7' '35.2']]\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "pd.DataFrame(cleaned_array).to_csv('cleaned.csv')"
+      ],
+      "metadata": {
+        "id": "RZltyMmD_E68"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "# Convert to OWL Format"
+      ],
+      "metadata": {
+        "id": "M9rH5mX9Mx7g"
+      }
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "# **CSV to Text**"
+      ],
+      "metadata": {
+        "id": "SqFdbM634H5w"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "import  jpype\n",
+        "import  asposecells\n",
+        "\n",
+        "\n",
+        "jpype.startJVM()\n",
+        "from asposecells.api import Workbook\n",
+        "\n",
+        "workbook = Workbook(\"/content/sample.csv\")\n",
+        "workbook.save(\"Output.docx\")\n",
+        "jpype.shutdownJVM()"
+      ],
+      "metadata": {
+        "id": "949GB9T1_Go7",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 373
+        },
+        "outputId": "d3bf9a55-8248-459c-8eb6-c2c67e5a84b3"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "error",
+          "ename": "ModuleNotFoundError",
+          "evalue": "ignored",
+          "traceback": [
+            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+            "\u001b[0;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)",
+            "\u001b[0;32m<ipython-input-52-0cc478de6e7d>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;32mimport\u001b[0m  \u001b[0mjpype\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0;32mimport\u001b[0m  \u001b[0masposecells\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0mjpype\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstartJVM\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+            "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'jpype'",
+            "",
+            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0;32m\nNOTE: If your import is failing due to a missing package, you can\nmanually install dependencies using either !pip or !apt.\n\nTo view examples of installing some common dependencies, click the\n\"Open Examples\" button below.\n\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n"
+          ],
+          "errorDetails": {
+            "actions": [
+              {
+                "action": "open_url",
+                "actionText": "Open Examples",
+                "url": "/notebooks/snippets/importing_libraries.ipynb"
+              }
+            ]
+          }
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [],
+      "metadata": {
+        "id": "eIGJDS7u4DLS"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [],
+      "metadata": {
+        "id": "ziHBaaCn4DN2"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "# Brighten Image (For Anyone dealing with PDFs created from scanned images)"
+      ],
+      "metadata": {
+        "id": "FIzj02CHqce7"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "from PIL import Image, ImageEnhance\n",
+        "\n",
+        "#read the image\n",
+        "im = Image.open(\"ext_im.jpg\")\n",
+        "\n",
+        "#image brightness enhancer\n",
+        "enhancer = ImageEnhance.Brightness(im)\n",
+        "\n",
+        "factor = 1 #gives original image\n",
+        "im_output = enhancer.enhance(factor)\n",
+        "im_output.save('ext_im-1.jpg')\n",
+        "\n",
+        "factor = 1.5## brightens the image\n",
+        "im_output = enhancer.enhance(factor)\n",
+        "im_output.save('ext_im-2.jpg')\n"
+      ],
+      "metadata": {
+        "id": "vnzqj5q34DQk"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [],
+      "metadata": {
+        "id": "arQSfE2br7YT"
+      },
+      "execution_count": null,
+      "outputs": []
+    }
+  ],
+  "metadata": {
+    "accelerator": "GPU",
+    "colab": {
+      "collapsed_sections": [
+        "E693Ela3qhLx",
+        "SqFdbM634H5w",
+        "FIzj02CHqce7"
+      ],
+      "provenance": []
+    },
+    "kernelspec": {
+      "display_name": "Python 3",
+      "name": "python3"
+    },
+    "language_info": {
+      "name": "python"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}