Inception_v3_fine_tune.ipynb

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  "metadata": {
    "colab": {
      "name": "Inception_v3 fine tune.ipynb",
      "version": "0.3.2",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "metadata": {
        "id": "sgPc1deAztKd",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "# InceptionV3 fine tune\n",
        "      -Pre-trained Model Approach\n",
        "\n",
        "              1.  Select Source Model. A pre-trained source model is chosen from available models. Many research institutions release models on large and challenging datasets that may be included in the pool of candidate models from which to choose from.\n",
        "              2.  Reuse Model. The model pre-trained model can then be used as the starting point for a model on the second task of interest. This may involve using all or parts of the model, depending on the modeling technique used.\n",
        "              3. Tune Model. Optionally, the model may need to be adapted or refined on the input-output pair data available for the task of interest.\n",
        "This second type of transfer learning is common in the field of deep learning."
      ]
    },
    {
      "metadata": {
        "id": "7J8YdJ0Lzrta",
        "colab_type": "code",
        "outputId": "fc1e1929-f828-4111-c580-ed5a5544b7f8",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 54
        }
      },
      "cell_type": "code",
      "source": [
        "from google.colab import files \n",
        "from google.colab import drive\n",
        "\n",
        "drive.mount('/content/drive/')"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Drive already mounted at /content/drive/; to attempt to forcibly remount, call drive.mount(\"/content/drive/\", force_remount=True).\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "cFcZJCqi3o3F",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "**Importing Kaggle.json**"
      ]
    },
    {
      "metadata": {
        "id": "8lVYNN-92C8q",
        "colab_type": "code",
        "outputId": "9eb8b419-b3a4-4035-c244-a31cb8cbc557",
        "colab": {
          "resources": {
            "http://localhost:8080/nbextensions/google.colab/files.js": {
              "data": 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              "status_text": ""
            }
          },
          "base_uri": "https://localhost:8080/",
          "height": 91
        }
      },
      "cell_type": "code",
      "source": [
        "files.upload()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "\n",
              "     <input type=\"file\" id=\"files-fe26d54e-e2f8-4916-82f1-17971a091068\" name=\"files[]\" multiple disabled />\n",
              "     <output id=\"result-fe26d54e-e2f8-4916-82f1-17971a091068\">\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 kaggle.json to kaggle.json\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'kaggle.json': b'{\"username\":\"blaizzy\",\"key\":\"1a94cbea93dd6fb8d2b83e57ab97c880\"}'}"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 8
        }
      ]
    },
    {
      "metadata": {
        "id": "3kThaXqK46sz",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "Set-up"
      ]
    },
    {
      "metadata": {
        "id": "S21WXnzh45-T",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "!mkdir -p ~/.kaggle"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "7D0Vy77Z4yR3",
        "colab_type": "code",
        "outputId": "c7e5d2ed-20f9-409c-939b-5a89534d931a",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "cell_type": "code",
      "source": [
        "!cp kaggle.json ~/.kaggle/\n",
        "!chmod 600 ~/.kaggle/kaggle.json\n",
        "!ls ~/.kaggle"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "kaggle.json\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "NeKNOUFO5t69",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "** Verify Json**"
      ]
    },
    {
      "metadata": {
        "id": "wKs3yrzi4ybL",
        "colab_type": "code",
        "outputId": "cd3b2ed9-fc89-49de-f8e9-f4bf0b9e54b5",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 68
        }
      },
      "cell_type": "code",
      "source": [
        "!ls -l ~/.kaggle\n",
        "!cat ~/.kaggle/kaggle.json"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "total 4\n",
            "-rw------- 1 root root 63 Mar  2 10:15 kaggle.json\n",
            "{\"username\":\"blaizzy\",\"key\":\"1a94cbea93dd6fb8d2b83e57ab97c880\"}"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "hSETiWo16A-r",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "**Install Kaggle packages**"
      ]
    },
    {
      "metadata": {
        "id": "EqiJ-Z3x50pt",
        "colab_type": "code",
        "outputId": "df353272-e380-4083-bce0-31b5a2aa9730",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 136
        }
      },
      "cell_type": "code",
      "source": [
        "!pip install -q kaggle \n",
        "!pip install -q kaggle-cli"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "\u001b[K    100% |████████████████████████████████| 81kB 5.1MB/s \n",
            "\u001b[K    100% |████████████████████████████████| 5.3MB 5.1MB/s \n",
            "\u001b[K    100% |████████████████████████████████| 92kB 26.3MB/s \n",
            "\u001b[K    100% |████████████████████████████████| 51kB 20.6MB/s \n",
            "\u001b[?25h  Building wheel for kaggle-cli (setup.py) ... \u001b[?25ldone\n",
            "\u001b[?25h  Building wheel for cliff (setup.py) ... \u001b[?25ldone\n",
            "\u001b[?25h  Building wheel for pyperclip (setup.py) ... \u001b[?25ldone\n",
            "\u001b[?25h"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "nKtnp1246OuI",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "**Kaggle datasets**"
      ]
    },
    {
      "metadata": {
        "id": "hN-CtTCO8TPU",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "import os \n",
        "\n",
        "os.chdir('/content/drive/My Drive/')\n",
        "# !mkdir nih-chest-xrays"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "lzTY5Twa6T0U",
        "colab_type": "code",
        "outputId": "43da0d00-6090-40d4-e90c-891c0a5a05c2",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 68
        }
      },
      "cell_type": "code",
      "source": [
        "!kaggle datasets download \"nih-chest-xrays/sample\""
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Downloading sample.zip to /content/drive/My Drive/nih-chest-xrays\n",
            "100% 2.09G/2.10G [00:35<00:00, 56.2MB/s]\n",
            "100% 2.10G/2.10G [00:35<00:00, 63.7MB/s]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "do4TmrbN-rIc",
        "colab_type": "code",
        "outputId": "f2cd0638-2d6d-41ce-e8f4-8dc5da8847a6",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 95336
        }
      },
      "cell_type": "code",
      "source": [
        "!unzip sample.zip"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Archive:  sample.zip\n",
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          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "TgdT9UelIw-Y",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "# Import"
      ]
    },
    {
      "metadata": {
        "id": "IazKNCANHgYN",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "from keras.applications.inception_v3 import InceptionV3\n",
        "from keras.preprocessing.image import ImageDataGenerator\n",
        "from keras.models import Model\n",
        "from keras.layers import Dense, GlobalAveragePooling2D, Dropout, Input\n",
        "from keras import backend as K\n",
        "import pandas as pd\n",
        "import sklearn as sk\n",
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt\n",
        "import matplotlib.gridspec as gridspec\n",
        "from glob import glob\n",
        "import numpy as np"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "yiDSwFeTIJe4",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "# EDA - Exploratory Data Analysis\n"
      ]
    },
    {
      "metadata": {
        "id": "ME8nmn2xIo9W",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "os.chdir('/content/drive/My Drive/nih-chest-xrays')\n",
        "df = pd.read_csv(\"sample_labels.csv\")\n"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "oxAQ8VFGMhPk",
        "colab_type": "code",
        "outputId": "2cf8696b-bcdc-4326-ebd1-82c15ada4a93",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "cell_type": "code",
      "source": [
        "# Get Image paths to append to our csv\n",
        "image_paths = {os.path.basename(x): x for x in \n",
        "                   glob(os.path.join('/content/drive/My Drive/nih-chest-xrays/images/', '*.png'))}\n",
        "print('Scans found:', len(image_paths), ', Total Headers', df.shape[0])"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Scans found: 5606 , Total Headers 5606\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "hch6QT2nORRS",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "df['paths'] = df['Image Index'].map(image_paths.get)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "JpiP2mCcKGy0",
        "colab_type": "code",
        "outputId": "ecbbb50f-79c5-4e45-ff77-49f595717104",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 411
        }
      },
      "cell_type": "code",
      "source": [
        "df.head()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Image Index</th>\n",
              "      <th>Finding Labels</th>\n",
              "      <th>Follow-up #</th>\n",
              "      <th>Patient ID</th>\n",
              "      <th>Patient Age</th>\n",
              "      <th>Patient Gender</th>\n",
              "      <th>View Position</th>\n",
              "      <th>OriginalImageWidth</th>\n",
              "      <th>OriginalImageHeight</th>\n",
              "      <th>OriginalImagePixelSpacing_x</th>\n",
              "      <th>OriginalImagePixelSpacing_y</th>\n",
              "      <th>paths</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>00000013_005.png</td>\n",
              "      <td>Emphysema|Infiltration|Pleural_Thickening|Pneu...</td>\n",
              "      <td>5</td>\n",
              "      <td>13</td>\n",
              "      <td>060Y</td>\n",
              "      <td>M</td>\n",
              "      <td>AP</td>\n",
              "      <td>3056</td>\n",
              "      <td>2544</td>\n",
              "      <td>0.139</td>\n",
              "      <td>0.139</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>00000013_026.png</td>\n",
              "      <td>Cardiomegaly|Emphysema</td>\n",
              "      <td>26</td>\n",
              "      <td>13</td>\n",
              "      <td>057Y</td>\n",
              "      <td>M</td>\n",
              "      <td>AP</td>\n",
              "      <td>2500</td>\n",
              "      <td>2048</td>\n",
              "      <td>0.168</td>\n",
              "      <td>0.168</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>00000017_001.png</td>\n",
              "      <td>No Finding</td>\n",
              "      <td>1</td>\n",
              "      <td>17</td>\n",
              "      <td>077Y</td>\n",
              "      <td>M</td>\n",
              "      <td>AP</td>\n",
              "      <td>2500</td>\n",
              "      <td>2048</td>\n",
              "      <td>0.168</td>\n",
              "      <td>0.168</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>00000030_001.png</td>\n",
              "      <td>Atelectasis</td>\n",
              "      <td>1</td>\n",
              "      <td>30</td>\n",
              "      <td>079Y</td>\n",
              "      <td>M</td>\n",
              "      <td>PA</td>\n",
              "      <td>2992</td>\n",
              "      <td>2991</td>\n",
              "      <td>0.143</td>\n",
              "      <td>0.143</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>00000032_001.png</td>\n",
              "      <td>Cardiomegaly|Edema|Effusion</td>\n",
              "      <td>1</td>\n",
              "      <td>32</td>\n",
              "      <td>055Y</td>\n",
              "      <td>F</td>\n",
              "      <td>AP</td>\n",
              "      <td>2500</td>\n",
              "      <td>2048</td>\n",
              "      <td>0.168</td>\n",
              "      <td>0.168</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "        Image Index                                     Finding Labels  \\\n",
              "0  00000013_005.png  Emphysema|Infiltration|Pleural_Thickening|Pneu...   \n",
              "1  00000013_026.png                             Cardiomegaly|Emphysema   \n",
              "2  00000017_001.png                                         No Finding   \n",
              "3  00000030_001.png                                        Atelectasis   \n",
              "4  00000032_001.png                        Cardiomegaly|Edema|Effusion   \n",
              "\n",
              "   Follow-up #  Patient ID Patient Age Patient Gender View Position  \\\n",
              "0            5          13        060Y              M            AP   \n",
              "1           26          13        057Y              M            AP   \n",
              "2            1          17        077Y              M            AP   \n",
              "3            1          30        079Y              M            PA   \n",
              "4            1          32        055Y              F            AP   \n",
              "\n",
              "   OriginalImageWidth  OriginalImageHeight  OriginalImagePixelSpacing_x  \\\n",
              "0                3056                 2544                        0.139   \n",
              "1                2500                 2048                        0.168   \n",
              "2                2500                 2048                        0.168   \n",
              "3                2992                 2991                        0.143   \n",
              "4                2500                 2048                        0.168   \n",
              "\n",
              "   OriginalImagePixelSpacing_y  \\\n",
              "0                        0.139   \n",
              "1                        0.168   \n",
              "2                        0.168   \n",
              "3                        0.143   \n",
              "4                        0.168   \n",
              "\n",
              "                                               paths  \n",
              "0  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "1  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "2  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "3  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "4  /content/drive/My Drive/nih-chest-xrays/images...  "
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 63
        }
      ]
    },
    {
      "metadata": {
        "id": "M4vujQ9hKOZw",
        "colab_type": "code",
        "outputId": "fdd2f540-6cd5-4d9b-be73-cd3f1a257c2e",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 235
        }
      },
      "cell_type": "code",
      "source": [
        "des_df = df.describe()\n",
        "des_df.T"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>count</th>\n",
              "      <th>mean</th>\n",
              "      <th>std</th>\n",
              "      <th>min</th>\n",
              "      <th>25%</th>\n",
              "      <th>50%</th>\n",
              "      <th>75%</th>\n",
              "      <th>max</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Follow-up #</th>\n",
              "      <td>5606.0</td>\n",
              "      <td>8.616661</td>\n",
              "      <td>15.565815</td>\n",
              "      <td>0.000</td>\n",
              "      <td>0.000</td>\n",
              "      <td>3.000</td>\n",
              "      <td>10.000</td>\n",
              "      <td>177.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Patient ID</th>\n",
              "      <td>5606.0</td>\n",
              "      <td>14330.617017</td>\n",
              "      <td>8411.477789</td>\n",
              "      <td>13.000</td>\n",
              "      <td>7289.000</td>\n",
              "      <td>13993.000</td>\n",
              "      <td>20655.500</td>\n",
              "      <td>30797.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>OriginalImageWidth</th>\n",
              "      <td>5606.0</td>\n",
              "      <td>2644.795755</td>\n",
              "      <td>347.188754</td>\n",
              "      <td>1362.000</td>\n",
              "      <td>2500.000</td>\n",
              "      <td>2542.000</td>\n",
              "      <td>2992.000</td>\n",
              "      <td>3266.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>OriginalImageHeight</th>\n",
              "      <td>5606.0</td>\n",
              "      <td>2491.087406</td>\n",
              "      <td>399.119063</td>\n",
              "      <td>966.000</td>\n",
              "      <td>2048.000</td>\n",
              "      <td>2544.000</td>\n",
              "      <td>2991.000</td>\n",
              "      <td>3056.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>OriginalImagePixelSpacing_x</th>\n",
              "      <td>5606.0</td>\n",
              "      <td>0.155467</td>\n",
              "      <td>0.016201</td>\n",
              "      <td>0.115</td>\n",
              "      <td>0.143</td>\n",
              "      <td>0.143</td>\n",
              "      <td>0.168</td>\n",
              "      <td>0.1988</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>OriginalImagePixelSpacing_y</th>\n",
              "      <td>5606.0</td>\n",
              "      <td>0.155467</td>\n",
              "      <td>0.016201</td>\n",
              "      <td>0.115</td>\n",
              "      <td>0.143</td>\n",
              "      <td>0.143</td>\n",
              "      <td>0.168</td>\n",
              "      <td>0.1988</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                              count          mean          std       min  \\\n",
              "Follow-up #                  5606.0      8.616661    15.565815     0.000   \n",
              "Patient ID                   5606.0  14330.617017  8411.477789    13.000   \n",
              "OriginalImageWidth           5606.0   2644.795755   347.188754  1362.000   \n",
              "OriginalImageHeight          5606.0   2491.087406   399.119063   966.000   \n",
              "OriginalImagePixelSpacing_x  5606.0      0.155467     0.016201     0.115   \n",
              "OriginalImagePixelSpacing_y  5606.0      0.155467     0.016201     0.115   \n",
              "\n",
              "                                  25%        50%        75%         max  \n",
              "Follow-up #                     0.000      3.000     10.000    177.0000  \n",
              "Patient ID                   7289.000  13993.000  20655.500  30797.0000  \n",
              "OriginalImageWidth           2500.000   2542.000   2992.000   3266.0000  \n",
              "OriginalImageHeight          2048.000   2544.000   2991.000   3056.0000  \n",
              "OriginalImagePixelSpacing_x     0.143      0.143      0.168      0.1988  \n",
              "OriginalImagePixelSpacing_y     0.143      0.143      0.168      0.1988  "
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 10
        }
      ]
    },
    {
      "metadata": {
        "id": "fWQFA2V-Oox5",
        "colab_type": "code",
        "outputId": "bf9a8993-3d72-4205-fb73-0710e86897d3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 567
        }
      },
      "cell_type": "code",
      "source": [
        "label_counts = df['Finding Labels'].value_counts()[:15]\n",
        "fig, ax1 = plt.subplots(1,1,figsize = (12, 8))\n",
        "ax1.bar(np.arange(len(label_counts))+0.5, label_counts)\n",
        "ax1.set_xticks(np.arange(len(label_counts))+0.5)\n",
        "_ = ax1.set_xticklabels(label_counts.index, rotation = 90)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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UZAAAAMBASQYAAAAMlGQAAADAQEkGAAAADJRkAAAAwEBJBgAAAAyUZAAAAMBASQYAAAAM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\n6KWXXpKfn59at25ti9+jt7y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IRSfutWvXTnfffbe2bdvmWl+8Ro0aGjNmjG07x3+DklxO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\nQmCC\n",
            "text/plain": [
              "<Figure size 864x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "id": "ihvzZ854PIgs",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "# df['Finding Labels'] = df['Finding Labels'].map(lambda x: x.replace('No Finding',''))\n",
        "from itertools import chain\n",
        "all_labels = np.unique(list(chain(*df['Finding Labels'].map(lambda x: x.split('|')).tolist())))\n",
        "all_labels = [x for x in all_labels if len(x)>0]\n",
        "# print('All Labels ({}): {}'.format(len(all_labels), all_labels))\n",
        "# for c_label in all_labels:\n",
        "#     if len(c_label)>1: # leave out empty labels\n",
        "#        df[c_label] = df['Finding Labels'].map(lambda finding: 1.0 if c_label in finding else 0)\n",
        "# df.sample(3)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "nXFn2FGiQEGb",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "# keep at least 1000 cases\n",
        "MIN_CASES = 100\n",
        "all_labels = [i for i in all_labels if df[i].sum()>MIN_CASES]\n",
        "\n",
        "print('Clean Labels ({})'.format(len(all_labels)),\n",
        "      [(c_label,int(df[c_label].sum())) for c_label in all_labels])"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "R8j5LpgyV1PP",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "#eliminating null values\n",
        "df = df[~df['Finding Labels'].str.contains('No Finding')]"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "9ROH5DuLJZPx",
        "colab_type": "code",
        "outputId": "103be210-42e1-4167-91fe-722098d38e86",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 4046
        }
      },
      "cell_type": "code",
      "source": [
        "df"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Image Index</th>\n",
              "      <th>Finding Labels</th>\n",
              "      <th>Follow-up #</th>\n",
              "      <th>Patient ID</th>\n",
              "      <th>Patient Age</th>\n",
              "      <th>Patient Gender</th>\n",
              "      <th>View Position</th>\n",
              "      <th>OriginalImageWidth</th>\n",
              "      <th>OriginalImageHeight</th>\n",
              "      <th>OriginalImagePixelSpacing_x</th>\n",
              "      <th>OriginalImagePixelSpacing_y</th>\n",
              "      <th>paths</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>00000013_005.png</td>\n",
              "      <td>Emphysema|Infiltration|Pleural_Thickening|Pneu...</td>\n",
              "      <td>5</td>\n",
              "      <td>13</td>\n",
              "      <td>060Y</td>\n",
              "      <td>M</td>\n",
              "      <td>AP</td>\n",
              "      <td>3056</td>\n",
              "      <td>2544</td>\n",
              "      <td>0.139000</td>\n",
              "      <td>0.139000</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>00000013_026.png</td>\n",
              "      <td>Cardiomegaly|Emphysema</td>\n",
              "      <td>26</td>\n",
              "      <td>13</td>\n",
              "      <td>057Y</td>\n",
              "      <td>M</td>\n",
              "      <td>AP</td>\n",
              "      <td>2500</td>\n",
              "      <td>2048</td>\n",
              "      <td>0.168000</td>\n",
              "      <td>0.168000</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>00000030_001.png</td>\n",
              "      <td>Atelectasis</td>\n",
              "      <td>1</td>\n",
              "      <td>30</td>\n",
              "      <td>079Y</td>\n",
              "      <td>M</td>\n",
              "      <td>PA</td>\n",
              "      <td>2992</td>\n",
              "      <td>2991</td>\n",
              "      <td>0.143000</td>\n",
              "      <td>0.143000</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>00000032_001.png</td>\n",
              "      <td>Cardiomegaly|Edema|Effusion</td>\n",
              "      <td>1</td>\n",
              "      <td>32</td>\n",
              "      <td>055Y</td>\n",
              "      <td>F</td>\n",
              "      <td>AP</td>\n",
              "      <td>2500</td>\n",
              "      <td>2048</td>\n",
              "      <td>0.168000</td>\n",
              "      <td>0.168000</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>00000040_003.png</td>\n",
              "      <td>Consolidation|Mass</td>\n",
              "      <td>3</td>\n",
              "      <td>40</td>\n",
              "      <td>068Y</td>\n",
              "      <td>M</td>\n",
              "      <td>PA</td>\n",
              "      <td>2500</td>\n",
              "      <td>2048</td>\n",
              "      <td>0.168000</td>\n",
              "      <td>0.168000</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>00000061_002.png</td>\n",
              "      <td>Effusion</td>\n",
              "      <td>2</td>\n",
              "      <td>61</td>\n",
              "      <td>077Y</td>\n",
              "      <td>M</td>\n",
              "      <td>PA</td>\n",
              "      <td>2992</td>\n",
              "      <td>2991</td>\n",
              "      <td>0.143000</td>\n",
              "      <td>0.143000</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>00000061_025.png</td>\n",
              "      <td>Consolidation|Effusion|Infiltration|Nodule</td>\n",
              "      <td>25</td>\n",
              "      <td>61</td>\n",
              "      <td>077Y</td>\n",
              "      <td>M</td>\n",
              "      <td>AP</td>\n",
              "      <td>3056</td>\n",
              "      <td>2544</td>\n",
              "      <td>0.139000</td>\n",
              "      <td>0.139000</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>00000079_000.png</td>\n",
              "      <td>Mass</td>\n",
              "      <td>0</td>\n",
              "      <td>79</td>\n",
              "      <td>063Y</td>\n",
              "      <td>M</td>\n",
              "      <td>PA</td>\n",
              "      <td>2500</td>\n",
              "      <td>2048</td>\n",
              "      <td>0.168000</td>\n",
              "      <td>0.168000</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>00000084_000.png</td>\n",
              "      <td>Effusion</td>\n",
              "      <td>0</td>\n",
              "      <td>84</td>\n",
              "      <td>057Y</td>\n",
              "      <td>F</td>\n",
              "      <td>PA</td>\n",
              "      <td>2048</td>\n",
              "      <td>2500</td>\n",
              "      <td>0.171000</td>\n",
              "      <td>0.171000</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>00000096_006.png</td>\n",
              "      <td>Effusion</td>\n",
              "      <td>6</td>\n",
              "      <td>96</td>\n",
              "      <td>067Y</td>\n",
              "      <td>F</td>\n",
              "      <td>PA</td>\n",
              "      <td>2242</td>\n",
              "      <td>2546</td>\n",
              "      <td>0.143000</td>\n",
              "      <td>0.143000</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>00000099_003.png</td>\n",
              "      <td>Effusion</td>\n",
              "      <td>3</td>\n",
              "      <td>99</td>\n",
              "      <td>056Y</td>\n",
              "      <td>F</td>\n",
              "      <td>PA</td>\n",
              "      <td>2830</td>\n",
              "      <td>2801</td>\n",
              "      <td>0.143000</td>\n",
              "      <td>0.143000</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>00000103_001.png</td>\n",
              "      <td>Mass|Pneumothorax</td>\n",
              "      <td>1</td>\n",
              "      <td>103</td>\n",
              "      <td>060Y</td>\n",
              "      <td>M</td>\n",
              "      <td>PA</td>\n",
              "      <td>2500</td>\n",
              "      <td>2048</td>\n",
              "      <td>0.168000</td>\n",
              "      <td>0.168000</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>00000116_013.png</td>\n",
              "      <td>Cardiomegaly|Consolidation</td>\n",
              "      <td>13</td>\n",
              "      <td>116</td>\n",
              "      <td>075Y</td>\n",
              "      <td>F</td>\n",
              "      <td>AP</td>\n",
              "      <td>2500</td>\n",
              "      <td>2048</td>\n",
              "      <td>0.168000</td>\n",
              "      <td>0.168000</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>00000116_019.png</td>\n",
              "      <td>Consolidation</td>\n",
              "      <td>19</td>\n",
              "      <td>116</td>\n",
              "      <td>075Y</td>\n",
              "      <td>F</td>\n",
              "      <td>AP</td>\n",
              "      <td>2500</td>\n",
              "      <td>2048</td>\n",
              "      <td>0.168000</td>\n",
              "      <td>0.168000</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>00000116_032.png</td>\n",
              "      <td>Cardiomegaly|Consolidation</td>\n",
              "      <td>32</td>\n",
              "      <td>116</td>\n",
              "      <td>075Y</td>\n",
              "      <td>F</td>\n",
              "      <td>AP</td>\n",
              "      <td>2500</td>\n",
              "      <td>2048</td>\n",
              "      <td>0.168000</td>\n",
              "      <td>0.168000</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>00000116_040.png</td>\n",
              "      <td>Cardiomegaly|Consolidation</td>\n",
              "      <td>40</td>\n",
              "      <td>116</td>\n",
              "      <td>075Y</td>\n",
              "      <td>F</td>\n",
              "      <td>AP</td>\n",
              "      <td>2500</td>\n",
              "      <td>2048</td>\n",
              "      <td>0.168000</td>\n",
              "      <td>0.168000</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>00000118_011.png</td>\n",
              "      <td>Pneumothorax</td>\n",
              "      <td>11</td>\n",
              "      <td>118</td>\n",
              "      <td>073Y</td>\n",
              "      <td>M</td>\n",
              "      <td>PA</td>\n",
              "      <td>2774</td>\n",
              "      <td>2991</td>\n",
              "      <td>0.143000</td>\n",
              "      <td>0.143000</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>00000127_007.png</td>\n",
              "      <td>Effusion</td>\n",
              "      <td>7</td>\n",
              "      <td>127</td>\n",
              "      <td>056Y</td>\n",
              "      <td>F</td>\n",
              "      <td>AP</td>\n",
              "      <td>2500</td>\n",
              "      <td>2048</td>\n",
              "      <td>0.168000</td>\n",
              "      <td>0.168000</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>00000132_002.png</td>\n",
              "      <td>Consolidation|Pleural_Thickening</td>\n",
              "      <td>2</td>\n",
              "      <td>132</td>\n",
              "      <td>060Y</td>\n",
              "      <td>F</td>\n",
              "      <td>PA</td>\n",
              "      <td>2750</td>\n",
              "      <td>2991</td>\n",
              "      <td>0.143000</td>\n",
              "      <td>0.143000</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>00000154_001.png</td>\n",
              "      <td>Infiltration|Nodule</td>\n",
              "      <td>1</td>\n",
              "      <td>154</td>\n",
              "      <td>056Y</td>\n",
              "      <td>F</td>\n",
              "      <td>PA</td>\n",
              "      <td>2048</td>\n",
              "      <td>2500</td>\n",
              "      <td>0.168000</td>\n",
              "      <td>0.168000</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>00000175_001.png</td>\n",
              "      <td>Atelectasis</td>\n",
              "      <td>1</td>\n",
              "      <td>175</td>\n",
              "      <td>060Y</td>\n",
              "      <td>M</td>\n",
              "      <td>AP</td>\n",
              "      <td>3056</td>\n",
              "      <td>2544</td>\n",
              "      <td>0.139000</td>\n",
              "      <td>0.139000</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30</th>\n",
              "      <td>00000175_002.png</td>\n",
              "      <td>Atelectasis</td>\n",
              "      <td>2</td>\n",
              "      <td>175</td>\n",
              "      <td>060Y</td>\n",
              "      <td>M</td>\n",
              "      <td>AP</td>\n",
              "      <td>3056</td>\n",
              "      <td>2544</td>\n",
              "      <td>0.139000</td>\n",
              "      <td>0.139000</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31</th>\n",
              "      <td>00000181_001.png</td>\n",
              "      <td>Fibrosis</td>\n",
              "      <td>1</td>\n",
              "      <td>181</td>\n",
              "      <td>047Y</td>\n",
              "      <td>F</td>\n",
              "      <td>PA</td>\n",
              "      <td>2500</td>\n",
              "      <td>2048</td>\n",
              "      <td>0.171000</td>\n",
              "      <td>0.171000</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>32</th>\n",
              "      <td>00000181_017.png</td>\n",
              "      <td>Infiltration</td>\n",
              "      <td>17</td>\n",
              "      <td>181</td>\n",
              "      <td>050Y</td>\n",
              "      <td>F</td>\n",
              "      <td>AP</td>\n",
              "      <td>2500</td>\n",
              "      <td>2048</td>\n",
              "      <td>0.168000</td>\n",
              "      <td>0.168000</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>33</th>\n",
              "      <td>00000181_035.png</td>\n",
              "      <td>Infiltration</td>\n",
              "      <td>35</td>\n",
              "      <td>181</td>\n",
              "      <td>050Y</td>\n",
              "      <td>F</td>\n",
              "      <td>AP</td>\n",
              "      <td>2500</td>\n",
              "      <td>2048</td>\n",
              "      <td>0.168000</td>\n",
              "      <td>0.168000</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38</th>\n",
              "      <td>00000232_000.png</td>\n",
              "      <td>Fibrosis</td>\n",
              "      <td>0</td>\n",
              "      <td>232</td>\n",
              "      <td>045Y</td>\n",
              "      <td>M</td>\n",
              "      <td>PA</td>\n",
              "      <td>2992</td>\n",
              "      <td>2991</td>\n",
              "      <td>0.143000</td>\n",
              "      <td>0.143000</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>40</th>\n",
              "      <td>00000242_000.png</td>\n",
              "      <td>Consolidation</td>\n",
              "      <td>0</td>\n",
              "      <td>242</td>\n",
              "      <td>061Y</td>\n",
              "      <td>F</td>\n",
              "      <td>PA</td>\n",
              "      <td>2544</td>\n",
              "      <td>3056</td>\n",
              "      <td>0.139000</td>\n",
              "      <td>0.139000</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>41</th>\n",
              "      <td>00000243_001.png</td>\n",
              "      <td>Emphysema</td>\n",
              "      <td>1</td>\n",
              "      <td>243</td>\n",
              "      <td>069Y</td>\n",
              "      <td>M</td>\n",
              "      <td>PA</td>\n",
              "      <td>2500</td>\n",
              "      <td>2048</td>\n",
              "      <td>0.168000</td>\n",
              "      <td>0.168000</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>44</th>\n",
              "      <td>00000246_011.png</td>\n",
              "      <td>Infiltration</td>\n",
              "      <td>11</td>\n",
              "      <td>246</td>\n",
              "      <td>051Y</td>\n",
              "      <td>M</td>\n",
              "      <td>PA</td>\n",
              "      <td>3056</td>\n",
              "      <td>2544</td>\n",
              "      <td>0.139000</td>\n",
              "      <td>0.139000</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>45</th>\n",
              "      <td>00000246_016.png</td>\n",
              "      <td>Consolidation|Mass</td>\n",
              "      <td>16</td>\n",
              "      <td>246</td>\n",
              "      <td>051Y</td>\n",
              "      <td>M</td>\n",
              "      <td>PA</td>\n",
              "      <td>3056</td>\n",
              "      <td>2544</td>\n",
              "      <td>0.139000</td>\n",
              "      <td>0.139000</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5546</th>\n",
              "      <td>00030247_010.png</td>\n",
              "      <td>Atelectasis</td>\n",
              "      <td>10</td>\n",
              "      <td>30247</td>\n",
              "      <td>054Y</td>\n",
              "      <td>M</td>\n",
              "      <td>AP</td>\n",
              "      <td>3056</td>\n",
              "      <td>2544</td>\n",
              "      <td>0.139000</td>\n",
              "      <td>0.139000</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5550</th>\n",
              "      <td>00030279_010.png</td>\n",
              "      <td>Pneumothorax</td>\n",
              "      <td>10</td>\n",
              "      <td>30279</td>\n",
              "      <td>072Y</td>\n",
              "      <td>M</td>\n",
              "      <td>AP</td>\n",
              "      <td>3056</td>\n",
              "      <td>2544</td>\n",
              "      <td>0.139000</td>\n",
              "      <td>0.139000</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5551</th>\n",
              "      <td>00030284_000.png</td>\n",
              "      <td>Atelectasis</td>\n",
              "      <td>0</td>\n",
              "      <td>30284</td>\n",
              "      <td>049Y</td>\n",
              "      <td>M</td>\n",
              "      <td>PA</td>\n",
              "      <td>2015</td>\n",
              "      <td>2021</td>\n",
              "      <td>0.194311</td>\n",
              "      <td>0.194311</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5554</th>\n",
              "      <td>00030301_000.png</td>\n",
              "      <td>Nodule</td>\n",
              "      <td>0</td>\n",
              "      <td>30301</td>\n",
              "      <td>053Y</td>\n",
              "      <td>F</td>\n",
              "      <td>PA</td>\n",
              "      <td>1918</td>\n",
              "      <td>2021</td>\n",
              "      <td>0.194311</td>\n",
              "      <td>0.194311</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5557</th>\n",
              "      <td>00030323_029.png</td>\n",
              "      <td>Infiltration|Pneumothorax</td>\n",
              "      <td>29</td>\n",
              "      <td>30323</td>\n",
              "      <td>031Y</td>\n",
              "      <td>F</td>\n",
              "      <td>AP</td>\n",
              "      <td>3056</td>\n",
              "      <td>2544</td>\n",
              "      <td>0.139000</td>\n",
              "      <td>0.139000</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5559</th>\n",
              "      <td>00030346_001.png</td>\n",
              "      <td>Atelectasis|Consolidation</td>\n",
              "      <td>1</td>\n",
              "      <td>30346</td>\n",
              "      <td>064Y</td>\n",
              "      <td>F</td>\n",
              "      <td>AP</td>\n",
              "      <td>3056</td>\n",
              "      <td>2544</td>\n",
              "      <td>0.139000</td>\n",
              "      <td>0.139000</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5561</th>\n",
              "      <td>00030370_006.png</td>\n",
              "      <td>Atelectasis|Effusion|Infiltration</td>\n",
              "      <td>6</td>\n",
              "      <td>30370</td>\n",
              "      <td>081Y</td>\n",
              "      <td>M</td>\n",
              "      <td>AP</td>\n",
              "      <td>2544</td>\n",
              "      <td>3056</td>\n",
              "      <td>0.139000</td>\n",
              "      <td>0.139000</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5565</th>\n",
              "      <td>00030398_000.png</td>\n",
              "      <td>Consolidation|Effusion|Pneumonia</td>\n",
              "      <td>0</td>\n",
              "      <td>30398</td>\n",
              "      <td>055Y</td>\n",
              "      <td>F</td>\n",
              "      <td>PA</td>\n",
              "      <td>1684</td>\n",
              "      <td>2021</td>\n",
              "      <td>0.194311</td>\n",
              "      <td>0.194311</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5566</th>\n",
              "      <td>00030408_005.png</td>\n",
              "      <td>Effusion|Infiltration</td>\n",
              "      <td>5</td>\n",
              "      <td>30408</td>\n",
              "      <td>067Y</td>\n",
              "      <td>M</td>\n",
              "      <td>AP</td>\n",
              "      <td>3056</td>\n",
              "      <td>2544</td>\n",
              "      <td>0.139000</td>\n",
              "      <td>0.139000</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5567</th>\n",
              "      <td>00030410_000.png</td>\n",
              "      <td>Atelectasis</td>\n",
              "      <td>0</td>\n",
              "      <td>30410</td>\n",
              "      <td>065Y</td>\n",
              "      <td>M</td>\n",
              "      <td>PA</td>\n",
              "      <td>2021</td>\n",
              "      <td>2021</td>\n",
              "      <td>0.194311</td>\n",
              "      <td>0.194311</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5568</th>\n",
              "      <td>00030410_002.png</td>\n",
              "      <td>Consolidation</td>\n",
              "      <td>2</td>\n",
              "      <td>30410</td>\n",
              "      <td>065Y</td>\n",
              "      <td>M</td>\n",
              "      <td>AP</td>\n",
              "      <td>3056</td>\n",
              "      <td>2544</td>\n",
              "      <td>0.139000</td>\n",
              "      <td>0.139000</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5571</th>\n",
              "      <td>00030419_001.png</td>\n",
              "      <td>Cardiomegaly|Effusion</td>\n",
              "      <td>1</td>\n",
              "      <td>30419</td>\n",
              "      <td>012Y</td>\n",
              "      <td>M</td>\n",
              "      <td>AP</td>\n",
              "      <td>3056</td>\n",
              "      <td>2544</td>\n",
              "      <td>0.139000</td>\n",
              "      <td>0.139000</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5573</th>\n",
              "      <td>00030430_000.png</td>\n",
              "      <td>Infiltration</td>\n",
              "      <td>0</td>\n",
              "      <td>30430</td>\n",
              "      <td>021Y</td>\n",
              "      <td>F</td>\n",
              "      <td>PA</td>\n",
              "      <td>1794</td>\n",
              "      <td>1940</td>\n",
              "      <td>0.194311</td>\n",
              "      <td>0.194311</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5574</th>\n",
              "      <td>00030434_000.png</td>\n",
              "      <td>Atelectasis</td>\n",
              "      <td>0</td>\n",
              "      <td>30434</td>\n",
              "      <td>053Y</td>\n",
              "      <td>M</td>\n",
              "      <td>PA</td>\n",
              "      <td>2021</td>\n",
              "      <td>2021</td>\n",
              "      <td>0.194308</td>\n",
              "      <td>0.194308</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5578</th>\n",
              "      <td>00030471_004.png</td>\n",
              "      <td>Infiltration</td>\n",
              "      <td>4</td>\n",
              "      <td>30471</td>\n",
              "      <td>054Y</td>\n",
              "      <td>F</td>\n",
              "      <td>AP</td>\n",
              "      <td>3056</td>\n",
              "      <td>2544</td>\n",
              "      <td>0.139000</td>\n",
              "      <td>0.139000</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5583</th>\n",
              "      <td>00030545_000.png</td>\n",
              "      <td>Infiltration</td>\n",
              "      <td>0</td>\n",
              "      <td>30545</td>\n",
              "      <td>062Y</td>\n",
              "      <td>F</td>\n",
              "      <td>PA</td>\n",
              "      <td>1743</td>\n",
              "      <td>1795</td>\n",
              "      <td>0.194314</td>\n",
              "      <td>0.194314</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5585</th>\n",
              "      <td>00030573_013.png</td>\n",
              "      <td>Effusion|Infiltration</td>\n",
              "      <td>13</td>\n",
              "      <td>30573</td>\n",
              "      <td>026Y</td>\n",
              "      <td>M</td>\n",
              "      <td>AP</td>\n",
              "      <td>3056</td>\n",
              "      <td>2544</td>\n",
              "      <td>0.139000</td>\n",
              "      <td>0.139000</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5587</th>\n",
              "      <td>00030606_013.png</td>\n",
              "      <td>Pneumothorax</td>\n",
              "      <td>13</td>\n",
              "      <td>30606</td>\n",
              "      <td>059Y</td>\n",
              "      <td>M</td>\n",
              "      <td>PA</td>\n",
              "      <td>2021</td>\n",
              "      <td>2021</td>\n",
              "      <td>0.194311</td>\n",
              "      <td>0.194311</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5588</th>\n",
              "      <td>00030609_021.png</td>\n",
              "      <td>Atelectasis|Infiltration</td>\n",
              "      <td>21</td>\n",
              "      <td>30609</td>\n",
              "      <td>006Y</td>\n",
              "      <td>M</td>\n",
              "      <td>AP</td>\n",
              "      <td>3056</td>\n",
              "      <td>2544</td>\n",
              "      <td>0.139000</td>\n",
              "      <td>0.139000</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5589</th>\n",
              "      <td>00030634_000.png</td>\n",
              "      <td>Effusion</td>\n",
              "      <td>0</td>\n",
              "      <td>30634</td>\n",
              "      <td>060Y</td>\n",
              "      <td>F</td>\n",
              "      <td>PA</td>\n",
              "      <td>2544</td>\n",
              "      <td>3056</td>\n",
              "      <td>0.139000</td>\n",
              "      <td>0.139000</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5590</th>\n",
              "      <td>00030635_002.png</td>\n",
              "      <td>Effusion|Pneumothorax</td>\n",
              "      <td>2</td>\n",
              "      <td>30635</td>\n",
              "      <td>051Y</td>\n",
              "      <td>F</td>\n",
              "      <td>PA</td>\n",
              "      <td>2021</td>\n",
              "      <td>2020</td>\n",
              "      <td>0.194311</td>\n",
              "      <td>0.194311</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5591</th>\n",
              "      <td>00030635_007.png</td>\n",
              "      <td>Atelectasis|Effusion|Infiltration</td>\n",
              "      <td>7</td>\n",
              "      <td>30635</td>\n",
              "      <td>050Y</td>\n",
              "      <td>F</td>\n",
              "      <td>AP</td>\n",
              "      <td>3056</td>\n",
              "      <td>2544</td>\n",
              "      <td>0.139000</td>\n",
              "      <td>0.139000</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5592</th>\n",
              "      <td>00030636_010.png</td>\n",
              "      <td>Pneumothorax</td>\n",
              "      <td>10</td>\n",
              "      <td>30636</td>\n",
              "      <td>046Y</td>\n",
              "      <td>M</td>\n",
              "      <td>PA</td>\n",
              "      <td>2021</td>\n",
              "      <td>2021</td>\n",
              "      <td>0.194311</td>\n",
              "      <td>0.194311</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5593</th>\n",
              "      <td>00030636_012.png</td>\n",
              "      <td>Consolidation</td>\n",
              "      <td>12</td>\n",
              "      <td>30636</td>\n",
              "      <td>046Y</td>\n",
              "      <td>M</td>\n",
              "      <td>PA</td>\n",
              "      <td>2020</td>\n",
              "      <td>2021</td>\n",
              "      <td>0.194311</td>\n",
              "      <td>0.194311</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5594</th>\n",
              "      <td>00030636_013.png</td>\n",
              "      <td>Atelectasis|Effusion|Pneumothorax</td>\n",
              "      <td>13</td>\n",
              "      <td>30636</td>\n",
              "      <td>046Y</td>\n",
              "      <td>M</td>\n",
              "      <td>PA</td>\n",
              "      <td>2021</td>\n",
              "      <td>2021</td>\n",
              "      <td>0.194311</td>\n",
              "      <td>0.194311</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5595</th>\n",
              "      <td>00030636_014.png</td>\n",
              "      <td>Atelectasis|Effusion|Pneumothorax</td>\n",
              "      <td>14</td>\n",
              "      <td>30636</td>\n",
              "      <td>046Y</td>\n",
              "      <td>M</td>\n",
              "      <td>PA</td>\n",
              "      <td>2021</td>\n",
              "      <td>2021</td>\n",
              "      <td>0.194311</td>\n",
              "      <td>0.194311</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5598</th>\n",
              "      <td>00030650_002.png</td>\n",
              "      <td>Infiltration|Pneumothorax</td>\n",
              "      <td>2</td>\n",
              "      <td>30650</td>\n",
              "      <td>067Y</td>\n",
              "      <td>M</td>\n",
              "      <td>PA</td>\n",
              "      <td>2020</td>\n",
              "      <td>2021</td>\n",
              "      <td>0.194314</td>\n",
              "      <td>0.194314</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5599</th>\n",
              "      <td>00030695_002.png</td>\n",
              "      <td>Atelectasis</td>\n",
              "      <td>2</td>\n",
              "      <td>30695</td>\n",
              "      <td>052Y</td>\n",
              "      <td>F</td>\n",
              "      <td>PA</td>\n",
              "      <td>2021</td>\n",
              "      <td>2021</td>\n",
              "      <td>0.194311</td>\n",
              "      <td>0.194311</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5602</th>\n",
              "      <td>00030786_005.png</td>\n",
              "      <td>Cardiomegaly|Effusion|Emphysema</td>\n",
              "      <td>5</td>\n",
              "      <td>30786</td>\n",
              "      <td>061Y</td>\n",
              "      <td>F</td>\n",
              "      <td>AP</td>\n",
              "      <td>3056</td>\n",
              "      <td>2544</td>\n",
              "      <td>0.139000</td>\n",
              "      <td>0.139000</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5603</th>\n",
              "      <td>00030789_000.png</td>\n",
              "      <td>Infiltration</td>\n",
              "      <td>0</td>\n",
              "      <td>30789</td>\n",
              "      <td>052Y</td>\n",
              "      <td>F</td>\n",
              "      <td>PA</td>\n",
              "      <td>2021</td>\n",
              "      <td>2021</td>\n",
              "      <td>0.194311</td>\n",
              "      <td>0.194311</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>2562 rows × 12 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "           Image Index                                     Finding Labels  \\\n",
              "0     00000013_005.png  Emphysema|Infiltration|Pleural_Thickening|Pneu...   \n",
              "1     00000013_026.png                             Cardiomegaly|Emphysema   \n",
              "3     00000030_001.png                                        Atelectasis   \n",
              "4     00000032_001.png                        Cardiomegaly|Edema|Effusion   \n",
              "5     00000040_003.png                                 Consolidation|Mass   \n",
              "8     00000061_002.png                                           Effusion   \n",
              "10    00000061_025.png         Consolidation|Effusion|Infiltration|Nodule   \n",
              "11    00000079_000.png                                               Mass   \n",
              "14    00000084_000.png                                           Effusion   \n",
              "15    00000096_006.png                                           Effusion   \n",
              "16    00000099_003.png                                           Effusion   \n",
              "18    00000103_001.png                                  Mass|Pneumothorax   \n",
              "19    00000116_013.png                         Cardiomegaly|Consolidation   \n",
              "20    00000116_019.png                                      Consolidation   \n",
              "21    00000116_032.png                         Cardiomegaly|Consolidation   \n",
              "22    00000116_040.png                         Cardiomegaly|Consolidation   \n",
              "23    00000118_011.png                                       Pneumothorax   \n",
              "25    00000127_007.png                                           Effusion   \n",
              "26    00000132_002.png                   Consolidation|Pleural_Thickening   \n",
              "27    00000154_001.png                                Infiltration|Nodule   \n",
              "29    00000175_001.png                                        Atelectasis   \n",
              "30    00000175_002.png                                        Atelectasis   \n",
              "31    00000181_001.png                                           Fibrosis   \n",
              "32    00000181_017.png                                       Infiltration   \n",
              "33    00000181_035.png                                       Infiltration   \n",
              "38    00000232_000.png                                           Fibrosis   \n",
              "40    00000242_000.png                                      Consolidation   \n",
              "41    00000243_001.png                                          Emphysema   \n",
              "44    00000246_011.png                                       Infiltration   \n",
              "45    00000246_016.png                                 Consolidation|Mass   \n",
              "...                ...                                                ...   \n",
              "5546  00030247_010.png                                        Atelectasis   \n",
              "5550  00030279_010.png                                       Pneumothorax   \n",
              "5551  00030284_000.png                                        Atelectasis   \n",
              "5554  00030301_000.png                                             Nodule   \n",
              "5557  00030323_029.png                          Infiltration|Pneumothorax   \n",
              "5559  00030346_001.png                          Atelectasis|Consolidation   \n",
              "5561  00030370_006.png                  Atelectasis|Effusion|Infiltration   \n",
              "5565  00030398_000.png                   Consolidation|Effusion|Pneumonia   \n",
              "5566  00030408_005.png                              Effusion|Infiltration   \n",
              "5567  00030410_000.png                                        Atelectasis   \n",
              "5568  00030410_002.png                                      Consolidation   \n",
              "5571  00030419_001.png                              Cardiomegaly|Effusion   \n",
              "5573  00030430_000.png                                       Infiltration   \n",
              "5574  00030434_000.png                                        Atelectasis   \n",
              "5578  00030471_004.png                                       Infiltration   \n",
              "5583  00030545_000.png                                       Infiltration   \n",
              "5585  00030573_013.png                              Effusion|Infiltration   \n",
              "5587  00030606_013.png                                       Pneumothorax   \n",
              "5588  00030609_021.png                           Atelectasis|Infiltration   \n",
              "5589  00030634_000.png                                           Effusion   \n",
              "5590  00030635_002.png                              Effusion|Pneumothorax   \n",
              "5591  00030635_007.png                  Atelectasis|Effusion|Infiltration   \n",
              "5592  00030636_010.png                                       Pneumothorax   \n",
              "5593  00030636_012.png                                      Consolidation   \n",
              "5594  00030636_013.png                  Atelectasis|Effusion|Pneumothorax   \n",
              "5595  00030636_014.png                  Atelectasis|Effusion|Pneumothorax   \n",
              "5598  00030650_002.png                          Infiltration|Pneumothorax   \n",
              "5599  00030695_002.png                                        Atelectasis   \n",
              "5602  00030786_005.png                    Cardiomegaly|Effusion|Emphysema   \n",
              "5603  00030789_000.png                                       Infiltration   \n",
              "\n",
              "      Follow-up #  Patient ID Patient Age Patient Gender View Position  \\\n",
              "0               5          13        060Y              M            AP   \n",
              "1              26          13        057Y              M            AP   \n",
              "3               1          30        079Y              M            PA   \n",
              "4               1          32        055Y              F            AP   \n",
              "5               3          40        068Y              M            PA   \n",
              "8               2          61        077Y              M            PA   \n",
              "10             25          61        077Y              M            AP   \n",
              "11              0          79        063Y              M            PA   \n",
              "14              0          84        057Y              F            PA   \n",
              "15              6          96        067Y              F            PA   \n",
              "16              3          99        056Y              F            PA   \n",
              "18              1         103        060Y              M            PA   \n",
              "19             13         116        075Y              F            AP   \n",
              "20             19         116        075Y              F            AP   \n",
              "21             32         116        075Y              F            AP   \n",
              "22             40         116        075Y              F            AP   \n",
              "23             11         118        073Y              M            PA   \n",
              "25              7         127        056Y              F            AP   \n",
              "26              2         132        060Y              F            PA   \n",
              "27              1         154        056Y              F            PA   \n",
              "29              1         175        060Y              M            AP   \n",
              "30              2         175        060Y              M            AP   \n",
              "31              1         181        047Y              F            PA   \n",
              "32             17         181        050Y              F            AP   \n",
              "33             35         181        050Y              F            AP   \n",
              "38              0         232        045Y              M            PA   \n",
              "40              0         242        061Y              F            PA   \n",
              "41              1         243        069Y              M            PA   \n",
              "44             11         246        051Y              M            PA   \n",
              "45             16         246        051Y              M            PA   \n",
              "...           ...         ...         ...            ...           ...   \n",
              "5546           10       30247        054Y              M            AP   \n",
              "5550           10       30279        072Y              M            AP   \n",
              "5551            0       30284        049Y              M            PA   \n",
              "5554            0       30301        053Y              F            PA   \n",
              "5557           29       30323        031Y              F            AP   \n",
              "5559            1       30346        064Y              F            AP   \n",
              "5561            6       30370        081Y              M            AP   \n",
              "5565            0       30398        055Y              F            PA   \n",
              "5566            5       30408        067Y              M            AP   \n",
              "5567            0       30410        065Y              M            PA   \n",
              "5568            2       30410        065Y              M            AP   \n",
              "5571            1       30419        012Y              M            AP   \n",
              "5573            0       30430        021Y              F            PA   \n",
              "5574            0       30434        053Y              M            PA   \n",
              "5578            4       30471        054Y              F            AP   \n",
              "5583            0       30545        062Y              F            PA   \n",
              "5585           13       30573        026Y              M            AP   \n",
              "5587           13       30606        059Y              M            PA   \n",
              "5588           21       30609        006Y              M            AP   \n",
              "5589            0       30634        060Y              F            PA   \n",
              "5590            2       30635        051Y              F            PA   \n",
              "5591            7       30635        050Y              F            AP   \n",
              "5592           10       30636        046Y              M            PA   \n",
              "5593           12       30636        046Y              M            PA   \n",
              "5594           13       30636        046Y              M            PA   \n",
              "5595           14       30636        046Y              M            PA   \n",
              "5598            2       30650        067Y              M            PA   \n",
              "5599            2       30695        052Y              F            PA   \n",
              "5602            5       30786        061Y              F            AP   \n",
              "5603            0       30789        052Y              F            PA   \n",
              "\n",
              "      OriginalImageWidth  OriginalImageHeight  OriginalImagePixelSpacing_x  \\\n",
              "0                   3056                 2544                     0.139000   \n",
              "1                   2500                 2048                     0.168000   \n",
              "3                   2992                 2991                     0.143000   \n",
              "4                   2500                 2048                     0.168000   \n",
              "5                   2500                 2048                     0.168000   \n",
              "8                   2992                 2991                     0.143000   \n",
              "10                  3056                 2544                     0.139000   \n",
              "11                  2500                 2048                     0.168000   \n",
              "14                  2048                 2500                     0.171000   \n",
              "15                  2242                 2546                     0.143000   \n",
              "16                  2830                 2801                     0.143000   \n",
              "18                  2500                 2048                     0.168000   \n",
              "19                  2500                 2048                     0.168000   \n",
              "20                  2500                 2048                     0.168000   \n",
              "21                  2500                 2048                     0.168000   \n",
              "22                  2500                 2048                     0.168000   \n",
              "23                  2774                 2991                     0.143000   \n",
              "25                  2500                 2048                     0.168000   \n",
              "26                  2750                 2991                     0.143000   \n",
              "27                  2048                 2500                     0.168000   \n",
              "29                  3056                 2544                     0.139000   \n",
              "30                  3056                 2544                     0.139000   \n",
              "31                  2500                 2048                     0.171000   \n",
              "32                  2500                 2048                     0.168000   \n",
              "33                  2500                 2048                     0.168000   \n",
              "38                  2992                 2991                     0.143000   \n",
              "40                  2544                 3056                     0.139000   \n",
              "41                  2500                 2048                     0.168000   \n",
              "44                  3056                 2544                     0.139000   \n",
              "45                  3056                 2544                     0.139000   \n",
              "...                  ...                  ...                          ...   \n",
              "5546                3056                 2544                     0.139000   \n",
              "5550                3056                 2544                     0.139000   \n",
              "5551                2015                 2021                     0.194311   \n",
              "5554                1918                 2021                     0.194311   \n",
              "5557                3056                 2544                     0.139000   \n",
              "5559                3056                 2544                     0.139000   \n",
              "5561                2544                 3056                     0.139000   \n",
              "5565                1684                 2021                     0.194311   \n",
              "5566                3056                 2544                     0.139000   \n",
              "5567                2021                 2021                     0.194311   \n",
              "5568                3056                 2544                     0.139000   \n",
              "5571                3056                 2544                     0.139000   \n",
              "5573                1794                 1940                     0.194311   \n",
              "5574                2021                 2021                     0.194308   \n",
              "5578                3056                 2544                     0.139000   \n",
              "5583                1743                 1795                     0.194314   \n",
              "5585                3056                 2544                     0.139000   \n",
              "5587                2021                 2021                     0.194311   \n",
              "5588                3056                 2544                     0.139000   \n",
              "5589                2544                 3056                     0.139000   \n",
              "5590                2021                 2020                     0.194311   \n",
              "5591                3056                 2544                     0.139000   \n",
              "5592                2021                 2021                     0.194311   \n",
              "5593                2020                 2021                     0.194311   \n",
              "5594                2021                 2021                     0.194311   \n",
              "5595                2021                 2021                     0.194311   \n",
              "5598                2020                 2021                     0.194314   \n",
              "5599                2021                 2021                     0.194311   \n",
              "5602                3056                 2544                     0.139000   \n",
              "5603                2021                 2021                     0.194311   \n",
              "\n",
              "      OriginalImagePixelSpacing_y  \\\n",
              "0                        0.139000   \n",
              "1                        0.168000   \n",
              "3                        0.143000   \n",
              "4                        0.168000   \n",
              "5                        0.168000   \n",
              "8                        0.143000   \n",
              "10                       0.139000   \n",
              "11                       0.168000   \n",
              "14                       0.171000   \n",
              "15                       0.143000   \n",
              "16                       0.143000   \n",
              "18                       0.168000   \n",
              "19                       0.168000   \n",
              "20                       0.168000   \n",
              "21                       0.168000   \n",
              "22                       0.168000   \n",
              "23                       0.143000   \n",
              "25                       0.168000   \n",
              "26                       0.143000   \n",
              "27                       0.168000   \n",
              "29                       0.139000   \n",
              "30                       0.139000   \n",
              "31                       0.171000   \n",
              "32                       0.168000   \n",
              "33                       0.168000   \n",
              "38                       0.143000   \n",
              "40                       0.139000   \n",
              "41                       0.168000   \n",
              "44                       0.139000   \n",
              "45                       0.139000   \n",
              "...                           ...   \n",
              "5546                     0.139000   \n",
              "5550                     0.139000   \n",
              "5551                     0.194311   \n",
              "5554                     0.194311   \n",
              "5557                     0.139000   \n",
              "5559                     0.139000   \n",
              "5561                     0.139000   \n",
              "5565                     0.194311   \n",
              "5566                     0.139000   \n",
              "5567                     0.194311   \n",
              "5568                     0.139000   \n",
              "5571                     0.139000   \n",
              "5573                     0.194311   \n",
              "5574                     0.194308   \n",
              "5578                     0.139000   \n",
              "5583                     0.194314   \n",
              "5585                     0.139000   \n",
              "5587                     0.194311   \n",
              "5588                     0.139000   \n",
              "5589                     0.139000   \n",
              "5590                     0.194311   \n",
              "5591                     0.139000   \n",
              "5592                     0.194311   \n",
              "5593                     0.194311   \n",
              "5594                     0.194311   \n",
              "5595                     0.194311   \n",
              "5598                     0.194314   \n",
              "5599                     0.194311   \n",
              "5602                     0.139000   \n",
              "5603                     0.194311   \n",
              "\n",
              "                                                  paths  \n",
              "0     /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "1     /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "3     /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "4     /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5     /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "8     /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "10    /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "11    /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "14    /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "15    /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "16    /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "18    /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "19    /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "20    /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "21    /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "22    /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "23    /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "25    /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "26    /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "27    /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "29    /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "30    /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "31    /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "32    /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "33    /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "38    /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "40    /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "41    /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "44    /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "45    /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "...                                                 ...  \n",
              "5546  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5550  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5551  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5554  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5557  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5559  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5561  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5565  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5566  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5567  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5568  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5571  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5573  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5574  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5578  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5583  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5585  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5587  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5588  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5589  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5590  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5591  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5592  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5593  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5594  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5595  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5598  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5599  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5602  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5603  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "\n",
              "[2562 rows x 12 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 65
        }
      ]
    },
    {
      "metadata": {
        "id": "R81cZe5WTBOh",
        "colab_type": "code",
        "outputId": "552fd72f-88ae-4b54-cbbf-743ea1b3e1f1",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 567
        }
      },
      "cell_type": "code",
      "source": [
        "\n",
        "# since the dataset is very unbiased, we can resample it to be a more reasonable collection\n",
        "# weight is 0.1 + number of findings\n",
        "sample_weights = df['Finding Labels'].map(lambda x: len(x.split('|')) if len(x)>100 else 0).values + 4e-2\n",
        "sample_weights /= sample_weights.sum()\n",
        "df =df.sample(2500, weights=sample_weights)\n",
        "\n",
        "label_counts = df['Finding Labels'].value_counts()[:15]\n",
        "fig, ax1 = plt.subplots(1,1,figsize = (12, 8))\n",
        "ax1.bar(np.arange(len(label_counts))+0.5, label_counts)\n",
        "ax1.set_xticks(np.arange(len(label_counts))+0.5)\n",
        "_ = ax1.set_xticklabels(label_counts.index, rotation = 90)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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AAIzldyW/6c0339R///tf5eTk6MUXX1SdOnX0yiuvKDc3V8HBwZo4caICAgK0cuVKxcXF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\nEJNFwzAhhBBCCDFZ/wdHNSnJ5H6RXAAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 864x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "id": "y7P45jMyKZ3A",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "# Part II\n",
        "\n",
        "\n",
        "1.   Gain more insights \n",
        "\n"
      ]
    },
    {
      "metadata": {
        "id": "oYIXEIVWMwjS",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "labels = pd.read_csv('sample_labels.csv')"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "FalpUJMKMeqC",
        "colab_type": "code",
        "outputId": "b8c790d4-2346-4c66-bf4e-cc0ba7bacc3a",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 679
        }
      },
      "cell_type": "code",
      "source": [
        "labels = labels[['Image Index','Finding Labels','Follow-up #','Patient ID','Patient Age','Patient Gender']]\n",
        "#create new columns for each decease\n",
        "pathology_list = ['Cardiomegaly','Emphysema','Effusion','Hernia','Nodule','Pneumothorax','Atelectasis','Pleural_Thickening','Mass','Edema','Consolidation','Infiltration','Fibrosis','Pneumonia']\n",
        "for pathology in pathology_list :\n",
        "    labels[pathology] = labels['Finding Labels'].apply(lambda x: 1 if pathology in x else 0)\n",
        "#remove Y after age\n",
        "labels['Age']=labels['Patient Age'].apply(lambda x: x[:-1]).astype(int)\n",
        "\n",
        "plt.figure(figsize=(15,10))\n",
        "gs = gridspec.GridSpec(8,1)\n",
        "ax1 = plt.subplot(gs[:7, :])\n",
        "ax2 = plt.subplot(gs[7, :])\n",
        "data1 = pd.melt(labels,\n",
        "             id_vars=['Patient Gender'],\n",
        "             value_vars = list(pathology_list),\n",
        "             var_name = 'Category',\n",
        "             value_name = 'Count')\n",
        "data1 = data1.loc[data1.Count>0]\n",
        "g=sns.countplot(y='Category',hue='Patient Gender',data=data1, ax=ax1, order = data1['Category'].value_counts().index)\n",
        "ax1.set( ylabel=\"\",xlabel=\"\")\n",
        "ax1.legend(fontsize=20)\n",
        "ax1.set_title('X Ray partition',fontsize=18);\n",
        "\n",
        "labels['Nothing']=labels['Finding Labels'].apply(lambda x: 1 if 'No Finding' in x else 0)\n",
        "\n",
        "data2 = pd.melt(labels,\n",
        "             id_vars=['Patient Gender'],\n",
        "             value_vars = list(['Nothing']),\n",
        "             var_name = 'Category',\n",
        "             value_name = 'Count')\n",
        "data2 = data2.loc[data2.Count>0]\n",
        "g=sns.countplot(y='Category',hue='Patient Gender',data=data2,ax=ax2)\n",
        "ax2.set( ylabel=\"\",xlabel=\"Number of infected patient\")\n",
        "ax2.legend('')\n",
        "plt.subplots_adjust(hspace=.5)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/seaborn/categorical.py:1468: FutureWarning: remove_na is deprecated and is a private function. Do not use.\n",
            "  stat_data = remove_na(group_data[hue_mask])\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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QIXI4HPL09NSDDz6oLVu2aOTIkcrJybni40VH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\nhFcAAAAAgOURXgEAAAAAlvd/S+mfpENpT3EAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 1080x720 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "id": "vbAjiyKWNouR",
        "colab_type": "code",
        "outputId": "f2c0ebe0-9a83-4a04-a572-1bc04e74fd7d",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 309
        }
      },
      "cell_type": "code",
      "source": [
        "df.head()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Image Index</th>\n",
              "      <th>Finding Labels</th>\n",
              "      <th>Follow-up #</th>\n",
              "      <th>Patient ID</th>\n",
              "      <th>Patient Age</th>\n",
              "      <th>Patient Gender</th>\n",
              "      <th>View Position</th>\n",
              "      <th>OriginalImageWidth</th>\n",
              "      <th>OriginalImageHeight</th>\n",
              "      <th>OriginalImagePixelSpacing_x</th>\n",
              "      <th>OriginalImagePixelSpacing_y</th>\n",
              "      <th>paths</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>4113</th>\n",
              "      <td>00020259_000.png</td>\n",
              "      <td>[Atelectasis, Fibrosis]</td>\n",
              "      <td>0</td>\n",
              "      <td>20259</td>\n",
              "      <td>052Y</td>\n",
              "      <td>F</td>\n",
              "      <td>PA</td>\n",
              "      <td>2516</td>\n",
              "      <td>2608</td>\n",
              "      <td>0.139</td>\n",
              "      <td>0.139</td>\n",
              "      <td>./images/00020259_000.png</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3116</th>\n",
              "      <td>00015375_004.png</td>\n",
              "      <td>[Pleural_Thickening]</td>\n",
              "      <td>4</td>\n",
              "      <td>15375</td>\n",
              "      <td>075Y</td>\n",
              "      <td>M</td>\n",
              "      <td>AP</td>\n",
              "      <td>2500</td>\n",
              "      <td>2048</td>\n",
              "      <td>0.168</td>\n",
              "      <td>0.168</td>\n",
              "      <td>./images/00015375_004.png</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>486</th>\n",
              "      <td>00002533_003.png</td>\n",
              "      <td>[Edema]</td>\n",
              "      <td>3</td>\n",
              "      <td>2533</td>\n",
              "      <td>021Y</td>\n",
              "      <td>M</td>\n",
              "      <td>AP</td>\n",
              "      <td>3056</td>\n",
              "      <td>2544</td>\n",
              "      <td>0.139</td>\n",
              "      <td>0.139</td>\n",
              "      <td>./images/00002533_003.png</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4149</th>\n",
              "      <td>00020405_003.png</td>\n",
              "      <td>[Infiltration]</td>\n",
              "      <td>3</td>\n",
              "      <td>20405</td>\n",
              "      <td>048Y</td>\n",
              "      <td>M</td>\n",
              "      <td>PA</td>\n",
              "      <td>2698</td>\n",
              "      <td>2991</td>\n",
              "      <td>0.143</td>\n",
              "      <td>0.143</td>\n",
              "      <td>./images/00020405_003.png</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4354</th>\n",
              "      <td>00021495_005.png</td>\n",
              "      <td>[Atelectasis, Consolidation, Effusion, Emphyse...</td>\n",
              "      <td>5</td>\n",
              "      <td>21495</td>\n",
              "      <td>022Y</td>\n",
              "      <td>M</td>\n",
              "      <td>AP</td>\n",
              "      <td>3056</td>\n",
              "      <td>2544</td>\n",
              "      <td>0.139</td>\n",
              "      <td>0.139</td>\n",
              "      <td>./images/00021495_005.png</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "           Image Index                                     Finding Labels  \\\n",
              "4113  00020259_000.png                            [Atelectasis, Fibrosis]   \n",
              "3116  00015375_004.png                               [Pleural_Thickening]   \n",
              "486   00002533_003.png                                            [Edema]   \n",
              "4149  00020405_003.png                                     [Infiltration]   \n",
              "4354  00021495_005.png  [Atelectasis, Consolidation, Effusion, Emphyse...   \n",
              "\n",
              "      Follow-up #  Patient ID Patient Age Patient Gender View Position  \\\n",
              "4113            0       20259        052Y              F            PA   \n",
              "3116            4       15375        075Y              M            AP   \n",
              "486             3        2533        021Y              M            AP   \n",
              "4149            3       20405        048Y              M            PA   \n",
              "4354            5       21495        022Y              M            AP   \n",
              "\n",
              "      OriginalImageWidth  OriginalImageHeight  OriginalImagePixelSpacing_x  \\\n",
              "4113                2516                 2608                        0.139   \n",
              "3116                2500                 2048                        0.168   \n",
              "486                 3056                 2544                        0.139   \n",
              "4149                2698                 2991                        0.143   \n",
              "4354                3056                 2544                        0.139   \n",
              "\n",
              "      OriginalImagePixelSpacing_y                      paths  \n",
              "4113                        0.139  ./images/00020259_000.png  \n",
              "3116                        0.168  ./images/00015375_004.png  \n",
              "486                         0.139  ./images/00002533_003.png  \n",
              "4149                        0.143  ./images/00020405_003.png  \n",
              "4354                        0.139  ./images/00021495_005.png  "
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 24
        }
      ]
    },
    {
      "metadata": {
        "id": "V5poKpu3K_jJ",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "**Drop useless collumns**"
      ]
    },
    {
      "metadata": {
        "id": "vvm9p6XkK-2s",
        "colab_type": "code",
        "outputId": "ba9cdfea-c183-402b-bc5f-f483f4cd6127",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1969
        }
      },
      "cell_type": "code",
      "source": [
        "df.drop(['Follow-up #','Patient ID','Patient Age','Patient Gender','View Position','OriginalImageWidth','OriginalImageHeight'\n",
        "         ,'OriginalImagePixelSpacing_x','OriginalImagePixelSpacing_y'], axis = 1)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Image Index</th>\n",
              "      <th>Finding Labels</th>\n",
              "      <th>paths</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>00000013_005.png</td>\n",
              "      <td>Emphysema|Infiltration|Pleural_Thickening|Pneu...</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>00000013_026.png</td>\n",
              "      <td>Cardiomegaly|Emphysema</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>00000030_001.png</td>\n",
              "      <td>Atelectasis</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>00000032_001.png</td>\n",
              "      <td>Cardiomegaly|Edema|Effusion</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>00000040_003.png</td>\n",
              "      <td>Consolidation|Mass</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>00000061_002.png</td>\n",
              "      <td>Effusion</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>00000061_025.png</td>\n",
              "      <td>Consolidation|Effusion|Infiltration|Nodule</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>00000079_000.png</td>\n",
              "      <td>Mass</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>00000084_000.png</td>\n",
              "      <td>Effusion</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>00000096_006.png</td>\n",
              "      <td>Effusion</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>00000099_003.png</td>\n",
              "      <td>Effusion</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>00000103_001.png</td>\n",
              "      <td>Mass|Pneumothorax</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>00000116_013.png</td>\n",
              "      <td>Cardiomegaly|Consolidation</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>00000116_019.png</td>\n",
              "      <td>Consolidation</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>00000116_032.png</td>\n",
              "      <td>Cardiomegaly|Consolidation</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>00000116_040.png</td>\n",
              "      <td>Cardiomegaly|Consolidation</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>00000118_011.png</td>\n",
              "      <td>Pneumothorax</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>00000127_007.png</td>\n",
              "      <td>Effusion</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>00000132_002.png</td>\n",
              "      <td>Consolidation|Pleural_Thickening</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>00000154_001.png</td>\n",
              "      <td>Infiltration|Nodule</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>00000175_001.png</td>\n",
              "      <td>Atelectasis</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30</th>\n",
              "      <td>00000175_002.png</td>\n",
              "      <td>Atelectasis</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31</th>\n",
              "      <td>00000181_001.png</td>\n",
              "      <td>Fibrosis</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>32</th>\n",
              "      <td>00000181_017.png</td>\n",
              "      <td>Infiltration</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>33</th>\n",
              "      <td>00000181_035.png</td>\n",
              "      <td>Infiltration</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38</th>\n",
              "      <td>00000232_000.png</td>\n",
              "      <td>Fibrosis</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>40</th>\n",
              "      <td>00000242_000.png</td>\n",
              "      <td>Consolidation</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>41</th>\n",
              "      <td>00000243_001.png</td>\n",
              "      <td>Emphysema</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>44</th>\n",
              "      <td>00000246_011.png</td>\n",
              "      <td>Infiltration</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>45</th>\n",
              "      <td>00000246_016.png</td>\n",
              "      <td>Consolidation|Mass</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5546</th>\n",
              "      <td>00030247_010.png</td>\n",
              "      <td>Atelectasis</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5550</th>\n",
              "      <td>00030279_010.png</td>\n",
              "      <td>Pneumothorax</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5551</th>\n",
              "      <td>00030284_000.png</td>\n",
              "      <td>Atelectasis</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5554</th>\n",
              "      <td>00030301_000.png</td>\n",
              "      <td>Nodule</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5557</th>\n",
              "      <td>00030323_029.png</td>\n",
              "      <td>Infiltration|Pneumothorax</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5559</th>\n",
              "      <td>00030346_001.png</td>\n",
              "      <td>Atelectasis|Consolidation</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5561</th>\n",
              "      <td>00030370_006.png</td>\n",
              "      <td>Atelectasis|Effusion|Infiltration</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5565</th>\n",
              "      <td>00030398_000.png</td>\n",
              "      <td>Consolidation|Effusion|Pneumonia</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5566</th>\n",
              "      <td>00030408_005.png</td>\n",
              "      <td>Effusion|Infiltration</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5567</th>\n",
              "      <td>00030410_000.png</td>\n",
              "      <td>Atelectasis</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5568</th>\n",
              "      <td>00030410_002.png</td>\n",
              "      <td>Consolidation</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5571</th>\n",
              "      <td>00030419_001.png</td>\n",
              "      <td>Cardiomegaly|Effusion</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5573</th>\n",
              "      <td>00030430_000.png</td>\n",
              "      <td>Infiltration</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5574</th>\n",
              "      <td>00030434_000.png</td>\n",
              "      <td>Atelectasis</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5578</th>\n",
              "      <td>00030471_004.png</td>\n",
              "      <td>Infiltration</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5583</th>\n",
              "      <td>00030545_000.png</td>\n",
              "      <td>Infiltration</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5585</th>\n",
              "      <td>00030573_013.png</td>\n",
              "      <td>Effusion|Infiltration</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5587</th>\n",
              "      <td>00030606_013.png</td>\n",
              "      <td>Pneumothorax</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5588</th>\n",
              "      <td>00030609_021.png</td>\n",
              "      <td>Atelectasis|Infiltration</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5589</th>\n",
              "      <td>00030634_000.png</td>\n",
              "      <td>Effusion</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5590</th>\n",
              "      <td>00030635_002.png</td>\n",
              "      <td>Effusion|Pneumothorax</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5591</th>\n",
              "      <td>00030635_007.png</td>\n",
              "      <td>Atelectasis|Effusion|Infiltration</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5592</th>\n",
              "      <td>00030636_010.png</td>\n",
              "      <td>Pneumothorax</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5593</th>\n",
              "      <td>00030636_012.png</td>\n",
              "      <td>Consolidation</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5594</th>\n",
              "      <td>00030636_013.png</td>\n",
              "      <td>Atelectasis|Effusion|Pneumothorax</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5595</th>\n",
              "      <td>00030636_014.png</td>\n",
              "      <td>Atelectasis|Effusion|Pneumothorax</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5598</th>\n",
              "      <td>00030650_002.png</td>\n",
              "      <td>Infiltration|Pneumothorax</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5599</th>\n",
              "      <td>00030695_002.png</td>\n",
              "      <td>Atelectasis</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5602</th>\n",
              "      <td>00030786_005.png</td>\n",
              "      <td>Cardiomegaly|Effusion|Emphysema</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5603</th>\n",
              "      <td>00030789_000.png</td>\n",
              "      <td>Infiltration</td>\n",
              "      <td>/content/drive/My Drive/nih-chest-xrays/images...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>2562 rows × 3 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "           Image Index                                     Finding Labels  \\\n",
              "0     00000013_005.png  Emphysema|Infiltration|Pleural_Thickening|Pneu...   \n",
              "1     00000013_026.png                             Cardiomegaly|Emphysema   \n",
              "3     00000030_001.png                                        Atelectasis   \n",
              "4     00000032_001.png                        Cardiomegaly|Edema|Effusion   \n",
              "5     00000040_003.png                                 Consolidation|Mass   \n",
              "8     00000061_002.png                                           Effusion   \n",
              "10    00000061_025.png         Consolidation|Effusion|Infiltration|Nodule   \n",
              "11    00000079_000.png                                               Mass   \n",
              "14    00000084_000.png                                           Effusion   \n",
              "15    00000096_006.png                                           Effusion   \n",
              "16    00000099_003.png                                           Effusion   \n",
              "18    00000103_001.png                                  Mass|Pneumothorax   \n",
              "19    00000116_013.png                         Cardiomegaly|Consolidation   \n",
              "20    00000116_019.png                                      Consolidation   \n",
              "21    00000116_032.png                         Cardiomegaly|Consolidation   \n",
              "22    00000116_040.png                         Cardiomegaly|Consolidation   \n",
              "23    00000118_011.png                                       Pneumothorax   \n",
              "25    00000127_007.png                                           Effusion   \n",
              "26    00000132_002.png                   Consolidation|Pleural_Thickening   \n",
              "27    00000154_001.png                                Infiltration|Nodule   \n",
              "29    00000175_001.png                                        Atelectasis   \n",
              "30    00000175_002.png                                        Atelectasis   \n",
              "31    00000181_001.png                                           Fibrosis   \n",
              "32    00000181_017.png                                       Infiltration   \n",
              "33    00000181_035.png                                       Infiltration   \n",
              "38    00000232_000.png                                           Fibrosis   \n",
              "40    00000242_000.png                                      Consolidation   \n",
              "41    00000243_001.png                                          Emphysema   \n",
              "44    00000246_011.png                                       Infiltration   \n",
              "45    00000246_016.png                                 Consolidation|Mass   \n",
              "...                ...                                                ...   \n",
              "5546  00030247_010.png                                        Atelectasis   \n",
              "5550  00030279_010.png                                       Pneumothorax   \n",
              "5551  00030284_000.png                                        Atelectasis   \n",
              "5554  00030301_000.png                                             Nodule   \n",
              "5557  00030323_029.png                          Infiltration|Pneumothorax   \n",
              "5559  00030346_001.png                          Atelectasis|Consolidation   \n",
              "5561  00030370_006.png                  Atelectasis|Effusion|Infiltration   \n",
              "5565  00030398_000.png                   Consolidation|Effusion|Pneumonia   \n",
              "5566  00030408_005.png                              Effusion|Infiltration   \n",
              "5567  00030410_000.png                                        Atelectasis   \n",
              "5568  00030410_002.png                                      Consolidation   \n",
              "5571  00030419_001.png                              Cardiomegaly|Effusion   \n",
              "5573  00030430_000.png                                       Infiltration   \n",
              "5574  00030434_000.png                                        Atelectasis   \n",
              "5578  00030471_004.png                                       Infiltration   \n",
              "5583  00030545_000.png                                       Infiltration   \n",
              "5585  00030573_013.png                              Effusion|Infiltration   \n",
              "5587  00030606_013.png                                       Pneumothorax   \n",
              "5588  00030609_021.png                           Atelectasis|Infiltration   \n",
              "5589  00030634_000.png                                           Effusion   \n",
              "5590  00030635_002.png                              Effusion|Pneumothorax   \n",
              "5591  00030635_007.png                  Atelectasis|Effusion|Infiltration   \n",
              "5592  00030636_010.png                                       Pneumothorax   \n",
              "5593  00030636_012.png                                      Consolidation   \n",
              "5594  00030636_013.png                  Atelectasis|Effusion|Pneumothorax   \n",
              "5595  00030636_014.png                  Atelectasis|Effusion|Pneumothorax   \n",
              "5598  00030650_002.png                          Infiltration|Pneumothorax   \n",
              "5599  00030695_002.png                                        Atelectasis   \n",
              "5602  00030786_005.png                    Cardiomegaly|Effusion|Emphysema   \n",
              "5603  00030789_000.png                                       Infiltration   \n",
              "\n",
              "                                                  paths  \n",
              "0     /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "1     /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "3     /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "4     /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5     /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "8     /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "10    /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "11    /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "14    /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "15    /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "16    /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "18    /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "19    /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "20    /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "21    /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "22    /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "23    /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "25    /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "26    /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "27    /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "29    /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "30    /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "31    /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "32    /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "33    /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "38    /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "40    /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "41    /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "44    /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "45    /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "...                                                 ...  \n",
              "5546  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5550  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5551  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5554  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5557  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5559  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5561  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5565  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5566  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5567  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5568  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5571  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5573  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5574  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5578  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5583  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5585  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5587  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5588  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5589  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5590  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5591  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5592  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5593  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5594  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5595  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5598  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5599  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5602  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "5603  /content/drive/My Drive/nih-chest-xrays/images...  \n",
              "\n",
              "[2562 rows x 3 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 66
        }
      ]
    },
    {
      "metadata": {
        "id": "S0NskoH4LneT",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "# Saving cleaned csv\n",
        "df.to_csv('/content/drive/My Drive/nih-chest-xrays/cleaned_sample.csv', index = False)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "HfGW144JKkj0",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "# Prepare data"
      ]
    },
    {
      "metadata": {
        "id": "0rSy0olwKsHv",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "# Creating a list of All labels\n",
        "df['Finding Labels'] = df['Finding Labels'].apply(lambda x: x.split('|'))"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "dIrL4tweVy3g",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "df = pd.read_csv('/content/drive/My Drive/nih-chest-xrays/cleaned_sample.csv')\n"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "Rs7BE64NZtpf",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "os.chdir('/content/drive/My Drive/nih-chest-xrays/')"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "EoSSJMOZMvKE",
        "colab_type": "code",
        "outputId": "c52b399f-7547-494a-8a69-b96df69771ff",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 68
        }
      },
      "cell_type": "code",
      "source": [
        "# Creating Image generators that will Augment my dataset \n",
        "datagen = ImageDataGenerator(rescale = 1./255., samplewise_center=True, \n",
        "                              samplewise_std_normalization=True, \n",
        "                              horizontal_flip = True, \n",
        "                              vertical_flip = False, \n",
        "                              height_shift_range= 0.05, \n",
        "                              width_shift_range=0.1, \n",
        "                              rotation_range=5, \n",
        "                              shear_range = 0.1,\n",
        "                              fill_mode = 'reflect',\n",
        "                              zoom_range=0.15)\n",
        "\n",
        "train_gen = datagen.flow_from_dataframe(\n",
        "dataframe = df[:1900],\n",
        "directory = '/content/drive/My Drive/nih-chest-xrays/',\n",
        "x_col ='paths',\n",
        "y_col ='Finding Labels',\n",
        "batch_size = 64,\n",
        "seed = 42,\n",
        "shuffle = True,\n",
        "class_mode = 'categorical',\n",
        "classes = ['Atelectasis','Cardiomegaly','Consolidation','Edema','Effusion',\n",
        "           'Emphysema', 'Fibrosis','Infiltration','Mass','Nodule','Pleural_Thickening',\n",
        "           'Pneumonia','Pneumothorax'],\n",
        "target_size = (299,299))\n",
        "\n",
        "\n",
        "valid_gen = datagen.flow_from_dataframe(\n",
        "dataframe = df[1900:2000],\n",
        "directory = '/content/drive/My Drive/nih-chest-xrays/',\n",
        "x_col ='paths',\n",
        "y_col ='Finding Labels',\n",
        "batch_size = 64,\n",
        "seed = 42,\n",
        "shuffle = True,\n",
        "class_mode = 'categorical',\n",
        "classes = ['Atelectasis','Cardiomegaly','Consolidation','Edema','Effusion',\n",
        "           'Emphysema', 'Fibrosis','Infiltration','Mass','Nodule','Pleural_Thickening',\n",
        "           'Pneumonia','Pneumothorax'],\n",
        "target_size = (299,299))\n",
        "\n",
        "test_gen = datagen.flow_from_dataframe(\n",
        "dataframe = df[2000:],\n",
        "directory = '/content/drive/My Drive/nih-chest-xrays/',\n",
        "x_col ='paths',\n",
        "y_col ='Finding Labels',\n",
        "batch_size = 64,\n",
        "seed = 42,\n",
        "shuffle = True,\n",
        "class_mode = 'categorical',\n",
        "classes = ['Atelectasis','Cardiomegaly','Consolidation','Edema','Effusion',\n",
        "           'Emphysema', 'Fibrosis','Infiltration','Mass','Nodule','Pleural_Thickening',\n",
        "           'Pneumonia','Pneumothorax'],\n",
        "target_size = (299,299))\n",
        "\n",
        "\n"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Found 1177 images belonging to 13 classes.\n",
            "Found 66 images belonging to 13 classes.\n",
            "Found 334 images belonging to 13 classes.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "pXxLAbhYRmLZ",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "# Build Model"
      ]
    },
    {
      "metadata": {
        "id": "rH_0WfXTRo-h",
        "colab_type": "code",
        "outputId": "57a0ecd4-e5c4-490d-e228-3654c64e94bb",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 139
        }
      },
      "cell_type": "code",
      "source": [
        "# Model\n",
        "input_tensor = Input(shape=(299, 299, 3))  \n",
        "base_model = InceptionV3(input_tensor = input_tensor,weights = 'imagenet', include_top= False)\n",
        "x = base_model.output\n",
        "x = GlobalAveragePooling2D()(x)\n",
        "x = Dense(2048, activation = 'relu')(x)\n",
        "drop = Dropout(0.5)(x)\n",
        "cl = Dense(13, activation = 'sigmoid')(drop)\n",
        "model = Model(inputs=input_tensor, outputs = cl )\n",
        "  \n",
        "for layer in base_model.layers:\n",
        "    layer.trainable = False\n",
        "    \n",
        "model.compile(optimizer = 'rmsprop', loss ='binary_crossentropy', metrics= ['accuracy'])\n",
        "\n",
        "# step_size\n",
        "STEP_SIZE_TRAIN = train_gen.n//train_gen.batch_size\n",
        "STEP_SIZE_VALID = valid_gen.n//valid_gen.batch_size\n",
        "STEP_SIZE_TEST = test_gen.n//test_gen.batch_size\n",
        "  \n",
        "\n",
        "# Training \n",
        "history = model.fit_generator(generator = train_gen, steps_per_epoch = train_step,\n",
        "                   validation_data = valid_gen,\n",
        "                   validation_steps = valid_step,\n",
        "                   epochs = 3)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Epoch 1/3\n",
            "18/18 [==============================] - 75s 4s/step - loss: 0.8139 - acc: 0.8770 - val_loss: 0.8784 - val_acc: 0.9231\n",
            "Epoch 2/3\n",
            "18/18 [==============================] - 42s 2s/step - loss: 0.4275 - acc: 0.9055 - val_loss: 0.5608 - val_acc: 0.8462\n",
            "Epoch 3/3\n",
            "18/18 [==============================] - 47s 3s/step - loss: 0.2934 - acc: 0.9113 - val_loss: 0.2542 - val_acc: 0.9195\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "qf3Ebw_5h-cS",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "# saving model\n",
        "model.save_weights('model.h5')"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "WFUYfP8uiuQE",
        "colab_type": "code",
        "outputId": "a2357f09-6284-48d3-d189-3ffeca012c49",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 207
        }
      },
      "cell_type": "code",
      "source": [
        "\n",
        "# Training \n",
        "history = model.fit_generator(generator = train_gen, steps_per_epoch = train_step,\n",
        "                   validation_data = valid_gen,\n",
        "                   validation_steps = valid_step,\n",
        "                   epochs = 5)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Epoch 1/5\n",
            "18/18 [==============================] - 54s 3s/step - loss: 0.2702 - acc: 0.9134 - val_loss: 0.2848 - val_acc: 0.9231\n",
            "Epoch 2/5\n",
            "18/18 [==============================] - 45s 3s/step - loss: 0.2623 - acc: 0.9180 - val_loss: 0.2798 - val_acc: 0.9231\n",
            "Epoch 3/5\n",
            "18/18 [==============================] - 47s 3s/step - loss: 0.2568 - acc: 0.9204 - val_loss: 0.2308 - val_acc: 0.9219\n",
            "Epoch 4/5\n",
            "18/18 [==============================] - 45s 2s/step - loss: 0.2537 - acc: 0.9212 - val_loss: 0.2786 - val_acc: 0.9231\n",
            "Epoch 5/5\n",
            "18/18 [==============================] - 47s 3s/step - loss: 0.2480 - acc: 0.9218 - val_loss: 0.2447 - val_acc: 0.9231\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "gsRlis7rnxn1",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "# saving model\n",
        "model.save_weights('model.h5')"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "MYkPLEDzn2y4",
        "colab_type": "code",
        "outputId": "6a14eb98-8e73-4d02-946a-3c3b318c3996",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 139
        }
      },
      "cell_type": "code",
      "source": [
        "# Training \n",
        "history = model.fit_generator(generator = train_gen, steps_per_epoch = train_step,\n",
        "                   validation_data = valid_gen,\n",
        "                   validation_steps = valid_step,\n",
        "                   epochs = 3)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Epoch 1/3\n",
            "18/18 [==============================] - 53s 3s/step - loss: 0.2461 - acc: 0.9215 - val_loss: 0.2245 - val_acc: 0.9219\n",
            "Epoch 2/3\n",
            "18/18 [==============================] - 45s 2s/step - loss: 0.2499 - acc: 0.9201 - val_loss: 0.2611 - val_acc: 0.9231\n",
            "Epoch 3/3\n",
            "18/18 [==============================] - 47s 3s/step - loss: 0.2473 - acc: 0.9231 - val_loss: 0.2307 - val_acc: 0.9231\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "3_v2V1tXokVw",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "model.save_weights('model.h5')"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "n-4DrN4VpPJy",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "for i, layer in enumerate(base_model.layers):\n",
        "   print(i, layer.name)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "u9Y2DKflpreg",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "for layer in model.layers[:249]:\n",
        "   layer.trainable = False\n",
        "for layer in model.layers[249:]:\n",
        "   layer.trainable = True"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "3OOiCVgnomJ8",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "from keras.optimizers import SGD\n",
        "model.compile(optimizer=SGD(lr=0.0001, momentum=0.9), loss ='binary_crossentropy', metrics= ['accuracy'])"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "Ro8TYjFFowgx",
        "colab_type": "code",
        "outputId": "3a443bca-4d2f-4f1e-f394-e76b48562d89",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 139
        }
      },
      "cell_type": "code",
      "source": [
        "history = model.fit_generator(generator = train_gen, steps_per_epoch = train_step,\n",
        "                   validation_data = valid_gen,\n",
        "                   validation_steps = valid_step,\n",
        "                   epochs = 3)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Epoch 1/3\n",
            "18/18 [==============================] - 81s 4s/step - loss: 0.2393 - acc: 0.9230 - val_loss: 0.2186 - val_acc: 0.9231\n",
            "Epoch 2/3\n",
            "18/18 [==============================] - 43s 2s/step - loss: 0.2384 - acc: 0.9227 - val_loss: 0.2296 - val_acc: 0.9231\n",
            "Epoch 3/3\n",
            "18/18 [==============================] - 48s 3s/step - loss: 0.2376 - acc: 0.9231 - val_loss: 0.2185 - val_acc: 0.9231\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "Wc-lbDAbqhl7",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "history = model.fit_generator(generator = train_gen, steps_per_epoch = train_step,\n",
        "                   validation_data = valid_gen,\n",
        "                   validation_steps = valid_step,\n",
        "                   epochs = 10)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "qngCf2NBrLdX",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "for layer in model.layers:\n",
        "   layer.trainable = True"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "_8vOTQILrnxE",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "from keras.optimizers import SGD\n",
        "model.compile(optimizer=SGD(lr=0.0001, momentum=0.9), loss ='binary_crossentropy', metrics= ['accuracy'])"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "q9xyc2Z9rY8v",
        "colab_type": "code",
        "outputId": "ab975176-3ed1-4860-84ab-a273e5329838",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 207
        }
      },
      "cell_type": "code",
      "source": [
        "\n",
        "history = model.fit_generator(generator = train_gen, steps_per_epoch = train_step,\n",
        "                   validation_data = valid_gen,\n",
        "                   validation_steps = valid_step,\n",
        "                   epochs = 5)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Epoch 1/5\n",
            "18/18 [==============================] - 109s 6s/step - loss: 0.2374 - acc: 0.9223 - val_loss: 0.2160 - val_acc: 0.9231\n",
            "Epoch 2/5\n",
            "18/18 [==============================] - 40s 2s/step - loss: 0.2372 - acc: 0.9231 - val_loss: 0.2441 - val_acc: 0.9231\n",
            "Epoch 3/5\n",
            "18/18 [==============================] - 58s 3s/step - loss: 0.2356 - acc: 0.9232 - val_loss: 0.2139 - val_acc: 0.9231\n",
            "Epoch 4/5\n",
            "18/18 [==============================] - 53s 3s/step - loss: 0.2363 - acc: 0.9229 - val_loss: 0.2377 - val_acc: 0.9231\n",
            "Epoch 5/5\n",
            "18/18 [==============================] - 55s 3s/step - loss: 0.2368 - acc: 0.9228 - val_loss: 0.2151 - val_acc: 0.9231\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "JYJQkMAss8Uh",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "results = model.evaluate_generator(generator = test_gen,\n",
        "                                   steps = STEP_SIZE_TEST)\n"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "LCzVJirzwo3i",
        "colab_type": "code",
        "outputId": "c0c6d07b-0232-4fce-d39f-320012160429",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "cell_type": "code",
      "source": [
        "print(results)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[0.22873518466949463, 0.9230769276618958]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "PnBeO8OnszIF",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "loss = history.history['loss']\n",
        "val_loss = history.history['val_loss']\n",
        "\n",
        "epochs = range(1, len(loss)+1)\n",
        "\n",
        "plt.plot(epochs, loss, 'bo', label = 'Training loss')\n",
        "plt.plot(epochs, val_loss, 'b', label = 'Validation loss')\n",
        "plt.title('Training and validation loss')\n",
        "plt.xlabel('Epochs')\n",
        "plt.ylabel('Loss')\n",
        "plt.legend()\n",
        "plt.show()"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "s7qjkHMvs_JC",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "acc = history.history['acc']\n",
        "val_acc = history.history['val_acc']\n",
        "\n",
        "plt.plot(epochs, acc, 'bo', label = 'Training acc')\n",
        "plt.plot(epochs, val_acc, 'b', label = 'Validation acc')\n",
        "plt.title('Training and validation accuracy')\n",
        "plt.xlabel('Epochs')\n",
        "plt.ylabel('Loss')\n",
        "plt.legend()\n",
        "plt.show()\n"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "M13ZyzNswvF_",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "os.chdir('/content/drive/My Drive/nih-chest-xrays/')\n",
        "input_tensor = Input(shape=(299, 299, 3))  \n",
        "base_model = InceptionV3(input_tensor = input_tensor,weights = 'imagenet', include_top= False)\n",
        "x = base_model.output\n",
        "x = GlobalAveragePooling2D()(x)\n",
        "x = Dense(2048, activation = 'relu')(x)\n",
        "drop = Dropout(0.5)(x)\n",
        "cl = Dense(13, activation = 'sigmoid')(drop)\n",
        "model = Model(inputs=input_tensor, outputs = cl )\n",
        "  \n",
        "\n",
        "model.load_weights('model.h5')"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "hXQkg_d9xKXQ",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "from keras.optimizers import SGD\n",
        "model.compile(optimizer=SGD(lr=0.0001, momentum=0.9), loss ='binary_crossentropy', metrics= ['accuracy'])\n",
        "pred = model.evaluate_generator(generator = test_gen,\n",
        "                                   steps = STEP_SIZE_TEST)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "NZ2S3SGs0BeA",
        "colab_type": "code",
        "outputId": "db98cc5b-634e-4867-85e7-c620125d01a4",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "cell_type": "code",
      "source": [
        "pred"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[0.24083469212055206, 0.9230769276618958]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 149
        }
      ]
    },
    {
      "metadata": {
        "id": "c1-0SYKxBE0l",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "# getting prections\n",
        "from keras.preprocessing import image\n",
        "import numpy as np\n",
        "img_path = '/content/drive/My Drive/nih-chest-xrays/images/00000030_001.png'\n",
        "img = image.load_img(img_path, target_size=(299, 299))\n",
        "x = image.img_to_array(img)\n",
        "x = np.expand_dims(x, axis=0)\n",
        "preds = model.predict(x)\n",
        "preds = preds.astype(float)*100\n"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "fibeqhhpIScY",
        "colab_type": "code",
        "outputId": "0e06801b-c996-4977-e52c-6bbe8ce4a248",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 68
        }
      },
      "cell_type": "code",
      "source": [
        "preds"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[ 9.83431637,  2.02944577,  1.44315064,  1.10289454, 15.49569368,\n",
              "         1.00281835,  2.72262394, 23.8225162 ,  6.67173862,  9.52925086,\n",
              "         4.00644243,  0.23866296,  5.4406248 ]])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 278
        }
      ]
    },
    {
      "metadata": {
        "id": "mAjMRYI555Z-",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "from sklearn.metrics import confusion_matrix\n",
        "\n",
        "y_true = train_gen.classes\n",
        "\n",
        "confusion_matrix(y_true, preds)"
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
}