Mapping_Context_Emotions_v4_to_v7.ipynb

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  "metadata": {
    "colab": {
      "name": "Mapping Context Emotions.ipynb",
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "TOsy4a5Ewt6J"
      },
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import random"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8zCslboMwzkU",
        "outputId": "eb65af7e-3c97-4c08-9730-af4c4115bcee"
      },
      "source": [
        "!wget https://raw.githubusercontent.com/juanluishg/dataproject4_models/main/datasets/emotics_annotations_clean_v4.csv"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "--2021-06-05 15:21:25--  https://raw.githubusercontent.com/juanluishg/dataproject4_models/main/datasets/emotics_annotations_clean_v4.csv\n",
            "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.108.133, 185.199.109.133, 185.199.110.133, ...\n",
            "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.108.133|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 22212982 (21M) [text/plain]\n",
            "Saving to: ‘emotics_annotations_clean_v4.csv’\n",
            "\n",
            "emotics_annotations 100%[===================>]  21.18M  50.8MB/s    in 0.4s    \n",
            "\n",
            "2021-06-05 15:21:26 (50.8 MB/s) - ‘emotics_annotations_clean_v4.csv’ saved [22212982/22212982]\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 569
        },
        "id": "-DvmOaorxIEd",
        "outputId": "96ff89d5-87de-43dc-a51c-1a7248af9787"
      },
      "source": [
        "df = pd.read_csv(\"emotics_annotations_clean_v4.csv\")\n",
        "df.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <th>valence</th>\n",
              "      <th>arousal</th>\n",
              "      <th>dominance</th>\n",
              "      <th>categories</th>\n",
              "      <th>n_cat</th>\n",
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              "  </thead>\n",
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              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>COCO_val2014_000000562243.jpg</td>\n",
              "      <td>mscoco/images</td>\n",
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              "      <td>[[ 86  58 564 628]]</td>\n",
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              "      <td>2.0</td>\n",
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              "      <td>COCO_train2014_000000288841.jpg</td>\n",
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              "      <td>(array([[array(['Anticipation'], dtype='&lt;U12')...</td>\n",
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              "      <td>Male</td>\n",
              "      <td>Adult</td>\n",
              "      <td>640.0</td>\n",
              "      <td>480.0</td>\n",
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              "      <td>605.0</td>\n",
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              "      <td>6.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>Anticipation</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>COCO_val2014_000000558171.jpg</td>\n",
              "      <td>mscoco/images</td>\n",
              "      <td>(array([[640]], dtype=uint16), array([[480]], ...</td>\n",
              "      <td>(array(['mscoco'], dtype='&lt;U6'), array([[(arra...</td>\n",
              "      <td>(array([[305,  92, 461, 465]], dtype=uint16), ...</td>\n",
              "      <td>[[305  92 461 465]]</td>\n",
              "      <td>(array([[array(['Engagement'], dtype='&lt;U10'),\\...</td>\n",
              "      <td>(array([[7]], dtype=uint8), array([[8]], dtype...</td>\n",
              "      <td>Male</td>\n",
              "      <td>Teenager</td>\n",
              "      <td>640.0</td>\n",
              "      <td>480.0</td>\n",
              "      <td>305.0</td>\n",
              "      <td>92.0</td>\n",
              "      <td>461.0</td>\n",
              "      <td>465.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>Engagement,Excitement,Happiness</td>\n",
              "      <td>3.0</td>\n",
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              "      <th>3</th>\n",
              "      <td>COCO_train2014_000000369575.jpg</td>\n",
              "      <td>mscoco/images</td>\n",
              "      <td>(array([[480]], dtype=uint16), array([[640]], ...</td>\n",
              "      <td>(array(['mscoco'], dtype='&lt;U6'), array([[(arra...</td>\n",
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              "      <td>(array([[8]], dtype=uint8), array([[9]], dtype...</td>\n",
              "      <td>Male</td>\n",
              "      <td>Kid</td>\n",
              "      <td>480.0</td>\n",
              "      <td>640.0</td>\n",
              "      <td>221.0</td>\n",
              "      <td>63.0</td>\n",
              "      <td>448.0</td>\n",
              "      <td>372.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>Aversion,Pleasure</td>\n",
              "      <td>2.0</td>\n",
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              "    <tr>\n",
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              "      <td>COCO_train2014_000000213009.jpg</td>\n",
              "      <td>mscoco/images</td>\n",
              "      <td>(array([[500]], dtype=uint16), array([[333]], ...</td>\n",
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              "      <td>7.0</td>\n",
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              "      <td>2.0</td>\n",
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            "text/plain": [
              "                          filename  ... n_cat\n",
              "0    COCO_val2014_000000562243.jpg  ...   2.0\n",
              "1  COCO_train2014_000000288841.jpg  ...   1.0\n",
              "2    COCO_val2014_000000558171.jpg  ...   3.0\n",
              "3  COCO_train2014_000000369575.jpg  ...   2.0\n",
              "4  COCO_train2014_000000213009.jpg  ...   2.0\n",
              "\n",
              "[5 rows x 21 columns]"
            ]
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          "metadata": {
            "tags": []
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          "execution_count": 3
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      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Q_tRnJ0uw1oZ"
      },
      "source": [
        "mapping = {\"Disapproval\": \"Angry\", \"Annoyance\": \"Angry\", \"Anger\": \"Angry\", \"Disquietment\": \"Angry\",\n",
        "\"Disconnection\": \"Disgust\", \"Fatigue\": \"Disgust\", \"Embarrassment\": \"Disgust\", \"Aversion\": \"Disgust\",\n",
        "\"Doubt/Confusion\": \"Fear\", \"Fear\" : \"Fear\",\n",
        "\"Confidence\": \"Happy\", \"Happiness\": \"Happy\", \"Pleasure\": \"Happy\", \"Excitement\": \"Happy\", \"Yearning\" : \"Happy\",\n",
        "\"Sadness\": \"Sad\", \"Pain\": \"Sad\", \"Suffering\" : \"Sad\", \n",
        "\"Anticipation\": \"Surprise\", \"Surprise\" : \"Surprise\",\n",
        "\"Peace\": \"Neutral\", \"Affection\": \"Neutral\", \"Esteem\": \"Neutral\", \"Engagement\": \"Neutral\", \"Sympathy\": \"Neutral\", \"Sensitivity\" : \"Neutral\"\n",
        "}"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2ZXAR1YzyN4i"
      },
      "source": [
        "df[\"cats\"] = df.categories.str.split(\",\")"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SjQO_thCzNwM"
      },
      "source": [
        "for i, row in df.iterrows():\n",
        "  phoenetic = [mapping[cat] for cat in row[\"cats\"]]\n",
        "  df.loc[i, \"mapping_cats\"] = ','.join(np.unique(np.array(phoenetic)))"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 569
        },
        "id": "3uZEeqCoz51i",
        "outputId": "a2b0843d-4ee1-4926-a4ff-8a22c4ef6e9f"
      },
      "source": [
        "df.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <th>filename</th>\n",
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              "      <th>gender</th>\n",
              "      <th>age</th>\n",
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              "      <th>x1</th>\n",
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              "      <th>y2</th>\n",
              "      <th>valence</th>\n",
              "      <th>arousal</th>\n",
              "      <th>dominance</th>\n",
              "      <th>categories</th>\n",
              "      <th>n_cat</th>\n",
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              "      <th>0</th>\n",
              "      <td>COCO_val2014_000000562243.jpg</td>\n",
              "      <td>mscoco/images</td>\n",
              "      <td>(array([[640]], dtype=uint16), array([[640]], ...</td>\n",
              "      <td>(array(['mscoco'], dtype='&lt;U6'), array([[(arra...</td>\n",
              "      <td>(array([[ 86,  58, 564, 628]], dtype=uint16), ...</td>\n",
              "      <td>[[ 86  58 564 628]]</td>\n",
              "      <td>(array([[array(['Disconnection'], dtype='&lt;U13'...</td>\n",
              "      <td>(array([[5]], dtype=uint8), array([[3]], dtype...</td>\n",
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              "      <td>Adult</td>\n",
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              "      <td>640.0</td>\n",
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              "      <td>564.0</td>\n",
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              "      <td>5.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>Disconnection,Doubt/Confusion</td>\n",
              "      <td>2.0</td>\n",
              "      <td>[Disconnection, Doubt/Confusion]</td>\n",
              "      <td>Disgust,Fear</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>COCO_train2014_000000288841.jpg</td>\n",
              "      <td>mscoco/images</td>\n",
              "      <td>(array([[640]], dtype=uint16), array([[480]], ...</td>\n",
              "      <td>(array(['mscoco'], dtype='&lt;U6'), array([[(arra...</td>\n",
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              "      <td>[[485 149 605 473]]</td>\n",
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              "      <td>Male</td>\n",
              "      <td>Adult</td>\n",
              "      <td>640.0</td>\n",
              "      <td>480.0</td>\n",
              "      <td>485.0</td>\n",
              "      <td>149.0</td>\n",
              "      <td>605.0</td>\n",
              "      <td>473.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>Anticipation</td>\n",
              "      <td>1.0</td>\n",
              "      <td>[Anticipation]</td>\n",
              "      <td>Surprise</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>COCO_val2014_000000558171.jpg</td>\n",
              "      <td>mscoco/images</td>\n",
              "      <td>(array([[640]], dtype=uint16), array([[480]], ...</td>\n",
              "      <td>(array(['mscoco'], dtype='&lt;U6'), array([[(arra...</td>\n",
              "      <td>(array([[305,  92, 461, 465]], dtype=uint16), ...</td>\n",
              "      <td>[[305  92 461 465]]</td>\n",
              "      <td>(array([[array(['Engagement'], dtype='&lt;U10'),\\...</td>\n",
              "      <td>(array([[7]], dtype=uint8), array([[8]], dtype...</td>\n",
              "      <td>Male</td>\n",
              "      <td>Teenager</td>\n",
              "      <td>640.0</td>\n",
              "      <td>480.0</td>\n",
              "      <td>305.0</td>\n",
              "      <td>92.0</td>\n",
              "      <td>461.0</td>\n",
              "      <td>465.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>Engagement,Excitement,Happiness</td>\n",
              "      <td>3.0</td>\n",
              "      <td>[Engagement, Excitement, Happiness]</td>\n",
              "      <td>Happy,Neutral</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>COCO_train2014_000000369575.jpg</td>\n",
              "      <td>mscoco/images</td>\n",
              "      <td>(array([[480]], dtype=uint16), array([[640]], ...</td>\n",
              "      <td>(array(['mscoco'], dtype='&lt;U6'), array([[(arra...</td>\n",
              "      <td>(array([[221,  63, 448, 372]], dtype=uint16), ...</td>\n",
              "      <td>[[221  63 448 372]]</td>\n",
              "      <td>(array([[array(['Aversion'], dtype='&lt;U8'),\\n  ...</td>\n",
              "      <td>(array([[8]], dtype=uint8), array([[9]], dtype...</td>\n",
              "      <td>Male</td>\n",
              "      <td>Kid</td>\n",
              "      <td>480.0</td>\n",
              "      <td>640.0</td>\n",
              "      <td>221.0</td>\n",
              "      <td>63.0</td>\n",
              "      <td>448.0</td>\n",
              "      <td>372.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>Aversion,Pleasure</td>\n",
              "      <td>2.0</td>\n",
              "      <td>[Aversion, Pleasure]</td>\n",
              "      <td>Disgust,Happy</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>COCO_train2014_000000213009.jpg</td>\n",
              "      <td>mscoco/images</td>\n",
              "      <td>(array([[500]], dtype=uint16), array([[333]], ...</td>\n",
              "      <td>(array(['mscoco'], dtype='&lt;U6'), array([[(arra...</td>\n",
              "      <td>(array([[ 44, 143, 150, 288]], dtype=uint16), ...</td>\n",
              "      <td>[[ 44 143 150 288]]</td>\n",
              "      <td>(array([[array(['Confidence'], dtype='&lt;U10'),\\...</td>\n",
              "      <td>(array([[7]], dtype=uint8), array([[9]], dtype...</td>\n",
              "      <td>Male</td>\n",
              "      <td>Adult</td>\n",
              "      <td>500.0</td>\n",
              "      <td>333.0</td>\n",
              "      <td>44.0</td>\n",
              "      <td>143.0</td>\n",
              "      <td>150.0</td>\n",
              "      <td>288.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>Confidence,Excitement</td>\n",
              "      <td>2.0</td>\n",
              "      <td>[Confidence, Excitement]</td>\n",
              "      <td>Happy</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                          filename  ...   mapping_cats\n",
              "0    COCO_val2014_000000562243.jpg  ...   Disgust,Fear\n",
              "1  COCO_train2014_000000288841.jpg  ...       Surprise\n",
              "2    COCO_val2014_000000558171.jpg  ...  Happy,Neutral\n",
              "3  COCO_train2014_000000369575.jpg  ...  Disgust,Happy\n",
              "4  COCO_train2014_000000213009.jpg  ...          Happy\n",
              "\n",
              "[5 rows x 23 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UwRJs6U10oqw"
      },
      "source": [
        "df.to_csv(\"emotics_annotations_clean_v6.csv\")"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8eNf_m4z6t2X"
      },
      "source": [
        "df = pd.read_csv(\"emotics_annotations_clean_v6.csv\")"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rOn8uQax2X5Z"
      },
      "source": [
        "df[\"mapping_cats\"] = df.mapping_cats.str.split(\",\")\n",
        "df[\"category\"] = \"\"\n",
        "for i, row in df.iterrows():\n",
        "  category = row[\"mapping_cats\"]\n",
        "  random_n = random.randint(0,len(category)-1)\n",
        "  df.loc[i, \"category\"] = category[random_n]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 586
        },
        "id": "hoCU8XFf6f09",
        "outputId": "1491bab0-e273-4bcc-a106-bba3d5e99931"
      },
      "source": [
        "df.head()"
      ],
      "execution_count": null,
      "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>Unnamed: 0</th>\n",
              "      <th>filename</th>\n",
              "      <th>folder</th>\n",
              "      <th>image_size</th>\n",
              "      <th>original_database</th>\n",
              "      <th>person</th>\n",
              "      <th>body_bbox</th>\n",
              "      <th>annotations_categories</th>\n",
              "      <th>annotations_continuous</th>\n",
              "      <th>gender</th>\n",
              "      <th>age</th>\n",
              "      <th>shape_x</th>\n",
              "      <th>shape_y</th>\n",
              "      <th>x1</th>\n",
              "      <th>y1</th>\n",
              "      <th>x2</th>\n",
              "      <th>y2</th>\n",
              "      <th>valence</th>\n",
              "      <th>arousal</th>\n",
              "      <th>dominance</th>\n",
              "      <th>categories</th>\n",
              "      <th>n_cat</th>\n",
              "      <th>cats</th>\n",
              "      <th>mapping_cats</th>\n",
              "      <th>category</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>COCO_val2014_000000562243.jpg</td>\n",
              "      <td>mscoco/images</td>\n",
              "      <td>(array([[640]], dtype=uint16), array([[640]], ...</td>\n",
              "      <td>(array(['mscoco'], dtype='&lt;U6'), array([[(arra...</td>\n",
              "      <td>(array([[ 86,  58, 564, 628]], dtype=uint16), ...</td>\n",
              "      <td>[[ 86  58 564 628]]</td>\n",
              "      <td>(array([[array(['Disconnection'], dtype='&lt;U13'...</td>\n",
              "      <td>(array([[5]], dtype=uint8), array([[3]], dtype...</td>\n",
              "      <td>Male</td>\n",
              "      <td>Adult</td>\n",
              "      <td>640.0</td>\n",
              "      <td>640.0</td>\n",
              "      <td>86.0</td>\n",
              "      <td>58.0</td>\n",
              "      <td>564.0</td>\n",
              "      <td>628.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>Disconnection,Doubt/Confusion</td>\n",
              "      <td>2.0</td>\n",
              "      <td>['Disconnection', 'Doubt/Confusion']</td>\n",
              "      <td>[Disgust, Fear]</td>\n",
              "      <td>Fear</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>COCO_train2014_000000288841.jpg</td>\n",
              "      <td>mscoco/images</td>\n",
              "      <td>(array([[640]], dtype=uint16), array([[480]], ...</td>\n",
              "      <td>(array(['mscoco'], dtype='&lt;U6'), array([[(arra...</td>\n",
              "      <td>(array([[485, 149, 605, 473]], dtype=uint16), ...</td>\n",
              "      <td>[[485 149 605 473]]</td>\n",
              "      <td>(array([[array(['Anticipation'], dtype='&lt;U12')...</td>\n",
              "      <td>(array([[6]], dtype=uint8), array([[4]], dtype...</td>\n",
              "      <td>Male</td>\n",
              "      <td>Adult</td>\n",
              "      <td>640.0</td>\n",
              "      <td>480.0</td>\n",
              "      <td>485.0</td>\n",
              "      <td>149.0</td>\n",
              "      <td>605.0</td>\n",
              "      <td>473.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>Anticipation</td>\n",
              "      <td>1.0</td>\n",
              "      <td>['Anticipation']</td>\n",
              "      <td>[Surprise]</td>\n",
              "      <td>Surprise</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2</td>\n",
              "      <td>COCO_val2014_000000558171.jpg</td>\n",
              "      <td>mscoco/images</td>\n",
              "      <td>(array([[640]], dtype=uint16), array([[480]], ...</td>\n",
              "      <td>(array(['mscoco'], dtype='&lt;U6'), array([[(arra...</td>\n",
              "      <td>(array([[305,  92, 461, 465]], dtype=uint16), ...</td>\n",
              "      <td>[[305  92 461 465]]</td>\n",
              "      <td>(array([[array(['Engagement'], dtype='&lt;U10'),\\...</td>\n",
              "      <td>(array([[7]], dtype=uint8), array([[8]], dtype...</td>\n",
              "      <td>Male</td>\n",
              "      <td>Teenager</td>\n",
              "      <td>640.0</td>\n",
              "      <td>480.0</td>\n",
              "      <td>305.0</td>\n",
              "      <td>92.0</td>\n",
              "      <td>461.0</td>\n",
              "      <td>465.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>Engagement,Excitement,Happiness</td>\n",
              "      <td>3.0</td>\n",
              "      <td>['Engagement', 'Excitement', 'Happiness']</td>\n",
              "      <td>[Happy, Neutral]</td>\n",
              "      <td>Neutral</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3</td>\n",
              "      <td>COCO_train2014_000000369575.jpg</td>\n",
              "      <td>mscoco/images</td>\n",
              "      <td>(array([[480]], dtype=uint16), array([[640]], ...</td>\n",
              "      <td>(array(['mscoco'], dtype='&lt;U6'), array([[(arra...</td>\n",
              "      <td>(array([[221,  63, 448, 372]], dtype=uint16), ...</td>\n",
              "      <td>[[221  63 448 372]]</td>\n",
              "      <td>(array([[array(['Aversion'], dtype='&lt;U8'),\\n  ...</td>\n",
              "      <td>(array([[8]], dtype=uint8), array([[9]], dtype...</td>\n",
              "      <td>Male</td>\n",
              "      <td>Kid</td>\n",
              "      <td>480.0</td>\n",
              "      <td>640.0</td>\n",
              "      <td>221.0</td>\n",
              "      <td>63.0</td>\n",
              "      <td>448.0</td>\n",
              "      <td>372.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>Aversion,Pleasure</td>\n",
              "      <td>2.0</td>\n",
              "      <td>['Aversion', 'Pleasure']</td>\n",
              "      <td>[Disgust, Happy]</td>\n",
              "      <td>Disgust</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>4</td>\n",
              "      <td>COCO_train2014_000000213009.jpg</td>\n",
              "      <td>mscoco/images</td>\n",
              "      <td>(array([[500]], dtype=uint16), array([[333]], ...</td>\n",
              "      <td>(array(['mscoco'], dtype='&lt;U6'), array([[(arra...</td>\n",
              "      <td>(array([[ 44, 143, 150, 288]], dtype=uint16), ...</td>\n",
              "      <td>[[ 44 143 150 288]]</td>\n",
              "      <td>(array([[array(['Confidence'], dtype='&lt;U10'),\\...</td>\n",
              "      <td>(array([[7]], dtype=uint8), array([[9]], dtype...</td>\n",
              "      <td>Male</td>\n",
              "      <td>Adult</td>\n",
              "      <td>500.0</td>\n",
              "      <td>333.0</td>\n",
              "      <td>44.0</td>\n",
              "      <td>143.0</td>\n",
              "      <td>150.0</td>\n",
              "      <td>288.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>Confidence,Excitement</td>\n",
              "      <td>2.0</td>\n",
              "      <td>['Confidence', 'Excitement']</td>\n",
              "      <td>[Happy]</td>\n",
              "      <td>Happy</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   Unnamed: 0                         filename  ...      mapping_cats  category\n",
              "0           0    COCO_val2014_000000562243.jpg  ...   [Disgust, Fear]      Fear\n",
              "1           1  COCO_train2014_000000288841.jpg  ...        [Surprise]  Surprise\n",
              "2           2    COCO_val2014_000000558171.jpg  ...  [Happy, Neutral]   Neutral\n",
              "3           3  COCO_train2014_000000369575.jpg  ...  [Disgust, Happy]   Disgust\n",
              "4           4  COCO_train2014_000000213009.jpg  ...           [Happy]     Happy\n",
              "\n",
              "[5 rows x 25 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 48
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pgV0mZTV7Rkg"
      },
      "source": [
        "df.to_csv(\"emotics_annotations_clean_v7.csv\")"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AERm7_l17esf"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}