DistractionDetector.ipynb

{
  "cells": [
    {
      "cell_type": "code",
      "execution_count": 49,
      "id": "8b381ee8",
      "metadata": {
        "id": "8b381ee8",
        "outputId": "26d0b9e2-04c2-466a-8ac3-db2096721833",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/gdrive\n"
          ]
        }
      ],
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/gdrive')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 50,
      "id": "c001bce3",
      "metadata": {
        "id": "c001bce3",
        "outputId": "edc7458c-1b98-4591-bd19-add365355c55",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "2.8.0\n"
          ]
        }
      ],
      "source": [
        "import tensorflow as tf\n",
        "from tensorflow.keras import Sequential\n",
        "from tensorflow.keras.layers import Flatten, Dense, Dropout, BatchNormalization\n",
        "from tensorflow.keras.layers import Conv1D, Conv2D, MaxPool2D\n",
        "from tensorflow.keras.optimizers import Adam\n",
        "print(tf.__version__)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 51,
      "id": "4a584539",
      "metadata": {
        "id": "4a584539"
      },
      "outputs": [],
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.preprocessing import StandardScaler,  LabelEncoder"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 52,
      "id": "e6a25ef2",
      "metadata": {
        "id": "e6a25ef2"
      },
      "outputs": [],
      "source": [
        "file = open('/content/gdrive/MyDrive/Training Data.csv')\n",
        "lines = file.readlines()\n",
        "\n",
        "processedList = []\n",
        "\n",
        "for i, line in enumerate(lines):\n",
        "        if i == 0:\n",
        "            continue\n",
        "        line = line.split(',')\n",
        "        l = len(line[3])\n",
        "        line[3] = line[3][:l-1]\n",
        "        temp = [line[0], line[1], line[2], line[3]]\n",
        "        processedList.append(temp)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 53,
      "id": "b16a5f4f",
      "metadata": {
        "id": "b16a5f4f",
        "outputId": "c2770d59-16e4-4ae1-acdc-fa299f1eec88",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
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              " ['Distracted', '0.5882', '-0.3644', '-0.7419'],\n",
              " ['Distracted', '-1.0578', '1.231', '-2.5979'],\n",
              " ['Distracted', '-1.1539', '2.2054', '-1.8033'],\n",
              " ['Distracted', '-0.345', '1.1265', '-1.0818'],\n",
              " ['Distracted', '0.9527', '0.3892', '-0.4359'],\n",
              " ['Distracted', '-0.2095', '0.889', '0.259'],\n",
              " ['Distracted', '0.2053', '-0.3922', '0.4538'],\n",
              " ['Distracted', '-1.4718', '0.244', '1.2841'],\n",
              " ['Distracted', '-1.2923', '-0.7914', '1.8149'],\n",
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              " ['Distracted', '-1.0947', '-1.1271', '0.2488'],\n",
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              " ['Distracted', '2.4538', '-0.0905', '4.8919'],\n",
              " ['Distracted', '-0.3218', '1.0631', '-3.0027'],\n",
              " ['Distracted', '-0.2062', '1.0318', '-5.3508'],\n",
              " ['Distracted', '1.9802', '-1.6605', '-4.1077'],\n",
              " ['Distracted', '-2.2902', '0.6161', '-2.4113'],\n",
              " ['Distracted', '-1.162', '0.789', '-1.0032'],\n",
              " ['Distracted', '-0.3848', '0.445', '-0.3104'],\n",
              " ['Distracted', '-0.1609', '1.3258', '-0.658'],\n",
              " ['Distracted', '-0.7177', '1.2076', '-0.7757'],\n",
              " ['Distracted', '-0.3873', '0.9514', '-1.1682'],\n",
              " ['Distracted', '-0.0831', '-0.4759', '3.833'],\n",
              " ['Distracted', '0.6699', '-1.8372', '1.2902'],\n",
              " ['Distracted', '-0.1718', '-0.8065', '0.3278'],\n",
              " ['Distracted', '0.9828', '-1.3692', '-0.3954'],\n",
              " ['Distracted', '0.6106', '-1.2491', '-1.687'],\n",
              " ['Distracted', '0.4796', '-0.2632', '-1.9915'],\n",
              " ...]"
            ]
          },
          "metadata": {},
          "execution_count": 53
        }
      ],
      "source": [
        "processedList"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 54,
      "id": "cef7b10a",
      "metadata": {
        "id": "cef7b10a"
      },
      "outputs": [],
      "source": [
        "columns = ['activity', 'ax', 'ay', 'az']"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 55,
      "id": "1723519f",
      "metadata": {
        "id": "1723519f",
        "outputId": "f87974e8-8191-4c12-9e66-5fe40faaeda4",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     activity       ax       ay       az\n",
              "0  Distracted   1.2171  -0.8719  -0.7159\n",
              "1  Distracted   0.4416  -0.5735  -1.0408\n",
              "2  Distracted   0.3688  -0.0624    -1.79\n",
              "3  Distracted   0.5882  -0.3644  -0.7419\n",
              "4  Distracted  -1.0578    1.231  -2.5979"
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              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 55
        }
      ],
      "source": [
        "data = pd.DataFrame(data = processedList, columns = columns)\n",
        "data.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 56,
      "id": "3782fb88",
      "metadata": {
        "id": "3782fb88",
        "outputId": "63b0be95-62d0-40f8-f9c4-17456e3e3efa",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(22796, 4)"
            ]
          },
          "metadata": {},
          "execution_count": 56
        }
      ],
      "source": [
        "data.shape"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 57,
      "id": "f6e5aea5",
      "metadata": {
        "id": "f6e5aea5",
        "outputId": "724dcaed-fc89-489f-a3f0-47c384537194",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 22796 entries, 0 to 22795\n",
            "Data columns (total 4 columns):\n",
            " #   Column    Non-Null Count  Dtype \n",
            "---  ------    --------------  ----- \n",
            " 0   activity  22796 non-null  object\n",
            " 1   ax        22796 non-null  object\n",
            " 2   ay        22796 non-null  object\n",
            " 3   az        22796 non-null  object\n",
            "dtypes: object(4)\n",
            "memory usage: 712.5+ KB\n"
          ]
        }
      ],
      "source": [
        "data.info()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 58,
      "id": "3528673c",
      "metadata": {
        "id": "3528673c",
        "outputId": "07e9009f-1589-4575-ea93-6e89f3b1863b",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Distracted    7764\n",
              "Drunk         7531\n",
              "Normal        7501\n",
              "Name: activity, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 58
        }
      ],
      "source": [
        "data['activity'].value_counts()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 59,
      "id": "cbbed146",
      "metadata": {
        "id": "cbbed146"
      },
      "outputs": [],
      "source": [
        "data['ax'] = data['ax'].astype('float')\n",
        "data['ay'] = data['ay'].astype('float')\n",
        "data['az'] = data['az'].astype('float')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 60,
      "id": "c77f0a73",
      "metadata": {
        "id": "c77f0a73",
        "outputId": "1dd04abb-5537-48e6-ea1c-70813d836ad7",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 22796 entries, 0 to 22795\n",
            "Data columns (total 4 columns):\n",
            " #   Column    Non-Null Count  Dtype  \n",
            "---  ------    --------------  -----  \n",
            " 0   activity  22796 non-null  object \n",
            " 1   ax        22796 non-null  float64\n",
            " 2   ay        22796 non-null  float64\n",
            " 3   az        22796 non-null  float64\n",
            "dtypes: float64(3), object(1)\n",
            "memory usage: 712.5+ KB\n"
          ]
        }
      ],
      "source": [
        "data.info()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 61,
      "id": "4e659b96",
      "metadata": {
        "id": "4e659b96",
        "outputId": "d1084a2a-02e8-4e7f-82c8-a4642a33e2e7",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Int64Index([  0,   1,   2,   3,   4,   5,   6,   7,   8,   9,\n",
            "            ...\n",
            "            190, 191, 192, 193, 194, 195, 196, 197, 198, 199],\n",
            "           dtype='int64', length=200)\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1080x504 with 3 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Int64Index([6500, 6501, 6502, 6503, 6504, 6505, 6506, 6507, 6508, 6509,\n",
            "            ...\n",
            "            6690, 6691, 6692, 6693, 6694, 6695, 6696, 6697, 6698, 6699],\n",
            "           dtype='int64', length=200)\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1080x504 with 3 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Int64Index([13001, 13002, 13003, 13004, 13005, 13006, 13007, 13008, 13009,\n",
            "            13010,\n",
            "            ...\n",
            "            13191, 13192, 13193, 13194, 13195, 13196, 13197, 13198, 13199,\n",
            "            13200],\n",
            "           dtype='int64', length=200)\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1080x504 with 3 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "source": [
        "Fs = 20\n",
        "activities = data['activity'].value_counts().index\n",
        "def plot_activity(activity, data):\n",
        "    print(data.index)\n",
        "    fig, (ax0, ax1, ax2) = plt.subplots(nrows = 3, figsize = (15, 7), sharex = True)\n",
        "    plot_axis (ax0, data.index, data['ax'], 'X-axis')\n",
        "    plot_axis (ax1, data.index, data['ay'], 'Y-axis')\n",
        "    plot_axis (ax2, data.index, data['az'], 'Z-axis')\n",
        "    plt.subplots_adjust(hspace = 0.2)\n",
        "    fig.suptitle(activity)\n",
        "    plt.subplots_adjust(top = 0.90)\n",
        "    plt.show()\n",
        "    \n",
        "def plot_axis(ax, x, y, title):\n",
        "    ax.plot(x, y, 'g');\n",
        "    ax.set_title(title)\n",
        "    ax.xaxis.set_visible(False)\n",
        "    ax.set_ylim([min(y) - np.std(y), max(y) + np.std(y)])\n",
        "    ax.set_xlim([min(x), max(x)])\n",
        "    ax.grid(True)\n",
        "    \n",
        "for activity in activities: \n",
        "    data_for_plot = data[data['activity'] == activity][:Fs*10]\n",
        "    plot_activity(activity, data_for_plot)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 62,
      "id": "f0eda359",
      "metadata": {
        "id": "f0eda359",
        "outputId": "3ddfb10d-1b5a-481d-e167-9520bca06a73",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     activity      ax      ay      az\n",
              "0  Distracted  1.2171 -0.8719 -0.7159\n",
              "1  Distracted  0.4416 -0.5735 -1.0408\n",
              "2  Distracted  0.3688 -0.0624 -1.7900\n",
              "3  Distracted  0.5882 -0.3644 -0.7419\n",
              "4  Distracted -1.0578  1.2310 -2.5979"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-7d3376d4-5c4f-4ff1-91c3-19e88a663a9b\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>activity</th>\n",
              "      <th>ax</th>\n",
              "      <th>ay</th>\n",
              "      <th>az</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Distracted</td>\n",
              "      <td>1.2171</td>\n",
              "      <td>-0.8719</td>\n",
              "      <td>-0.7159</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Distracted</td>\n",
              "      <td>0.4416</td>\n",
              "      <td>-0.5735</td>\n",
              "      <td>-1.0408</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Distracted</td>\n",
              "      <td>0.3688</td>\n",
              "      <td>-0.0624</td>\n",
              "      <td>-1.7900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Distracted</td>\n",
              "      <td>0.5882</td>\n",
              "      <td>-0.3644</td>\n",
              "      <td>-0.7419</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Distracted</td>\n",
              "      <td>-1.0578</td>\n",
              "      <td>1.2310</td>\n",
              "      <td>-2.5979</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-7d3376d4-5c4f-4ff1-91c3-19e88a663a9b')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
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              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
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              "      display: none;\n",
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              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
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              "          document.querySelector('#df-7d3376d4-5c4f-4ff1-91c3-19e88a663a9b button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-7d3376d4-5c4f-4ff1-91c3-19e88a663a9b');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 62
        }
      ],
      "source": [
        "df = data\n",
        "df.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 63,
      "id": "4882461f",
      "metadata": {
        "id": "4882461f"
      },
      "outputs": [],
      "source": [
        "Distracted = df[df['activity'] == 'Distracted'].copy()\n",
        "Drunk = df[df['activity'] == 'Drunk'].copy()\n",
        "Normal = df[df['activity'] == 'Normal'].copy()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 64,
      "id": "d3563052",
      "metadata": {
        "id": "d3563052",
        "outputId": "50ad0afc-ff92-4ba0-e616-5d2b40141d1a",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(22796, 4)"
            ]
          },
          "metadata": {},
          "execution_count": 64
        }
      ],
      "source": [
        "balanced_data = df\n",
        "balanced_data.shape"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 65,
      "id": "97a3942a",
      "metadata": {
        "id": "97a3942a",
        "outputId": "8b21a4da-da1b-4f15-bd12-edb30eee1719",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     activity      ax      ay      az\n",
              "0  Distracted  1.2171 -0.8719 -0.7159\n",
              "1  Distracted  0.4416 -0.5735 -1.0408\n",
              "2  Distracted  0.3688 -0.0624 -1.7900\n",
              "3  Distracted  0.5882 -0.3644 -0.7419\n",
              "4  Distracted -1.0578  1.2310 -2.5979"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-81b65df9-a3d6-4eb1-90de-7b57748fd97f\">\n",
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              "      <th></th>\n",
              "      <th>activity</th>\n",
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              "      <th>ay</th>\n",
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              "      <td>-0.8719</td>\n",
              "      <td>-0.7159</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Distracted</td>\n",
              "      <td>0.4416</td>\n",
              "      <td>-0.5735</td>\n",
              "      <td>-1.0408</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Distracted</td>\n",
              "      <td>0.3688</td>\n",
              "      <td>-0.0624</td>\n",
              "      <td>-1.7900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Distracted</td>\n",
              "      <td>0.5882</td>\n",
              "      <td>-0.3644</td>\n",
              "      <td>-0.7419</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Distracted</td>\n",
              "      <td>-1.0578</td>\n",
              "      <td>1.2310</td>\n",
              "      <td>-2.5979</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-81b65df9-a3d6-4eb1-90de-7b57748fd97f')\"\n",
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              "              style=\"display:none;\">\n",
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              "  </svg>\n",
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              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
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              "      border-radius: 50%;\n",
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              "      display: none;\n",
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              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
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              "    }\n",
              "  </style>\n",
              "\n",
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              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-81b65df9-a3d6-4eb1-90de-7b57748fd97f');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 65
        }
      ],
      "source": [
        "balanced_data.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 66,
      "id": "df4c100b",
      "metadata": {
        "id": "df4c100b"
      },
      "outputs": [],
      "source": [
        "from sklearn.preprocessing import LabelEncoder"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 67,
      "id": "b052999b",
      "metadata": {
        "id": "b052999b",
        "outputId": "bdf0bc01-bf5f-4ad0-c95d-a29bf5752727",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "         activity      ax      ay      az  label\n",
              "0      Distracted  1.2171 -0.8719 -0.7159      0\n",
              "1      Distracted  0.4416 -0.5735 -1.0408      0\n",
              "2      Distracted  0.3688 -0.0624 -1.7900      0\n",
              "3      Distracted  0.5882 -0.3644 -0.7419      0\n",
              "4      Distracted -1.0578  1.2310 -2.5979      0\n",
              "...           ...     ...     ...     ...    ...\n",
              "22791      Normal  1.2224  0.0378 -0.4226      2\n",
              "22792      Normal  1.2245 -0.6322  0.3700      2\n",
              "22793      Normal  1.3598 -0.1283 -0.6651      2\n",
              "22794      Normal  0.8097  0.6830 -0.7794      2\n",
              "22795      Normal -1.2318  1.4323  1.9648      2\n",
              "\n",
              "[22796 rows x 5 columns]"
            ],
            "text/html": [
              "\n",
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              "      <th></th>\n",
              "      <th>activity</th>\n",
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              "      <td>-0.7159</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Distracted</td>\n",
              "      <td>0.4416</td>\n",
              "      <td>-0.5735</td>\n",
              "      <td>-1.0408</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Distracted</td>\n",
              "      <td>0.3688</td>\n",
              "      <td>-0.0624</td>\n",
              "      <td>-1.7900</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Distracted</td>\n",
              "      <td>0.5882</td>\n",
              "      <td>-0.3644</td>\n",
              "      <td>-0.7419</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Distracted</td>\n",
              "      <td>-1.0578</td>\n",
              "      <td>1.2310</td>\n",
              "      <td>-2.5979</td>\n",
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              "      <th>...</th>\n",
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              "      <th>22791</th>\n",
              "      <td>Normal</td>\n",
              "      <td>1.2224</td>\n",
              "      <td>0.0378</td>\n",
              "      <td>-0.4226</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22792</th>\n",
              "      <td>Normal</td>\n",
              "      <td>1.2245</td>\n",
              "      <td>-0.6322</td>\n",
              "      <td>0.3700</td>\n",
              "      <td>2</td>\n",
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              "    <tr>\n",
              "      <th>22793</th>\n",
              "      <td>Normal</td>\n",
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              "      <td>-0.6651</td>\n",
              "      <td>2</td>\n",
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              "      <th>22794</th>\n",
              "      <td>Normal</td>\n",
              "      <td>0.8097</td>\n",
              "      <td>0.6830</td>\n",
              "      <td>-0.7794</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22795</th>\n",
              "      <td>Normal</td>\n",
              "      <td>-1.2318</td>\n",
              "      <td>1.4323</td>\n",
              "      <td>1.9648</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>22796 rows × 5 columns</p>\n",
              "</div>\n",
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              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-2d329e26-7b65-4867-a3b9-e05bc2d8bf69 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-2d329e26-7b65-4867-a3b9-e05bc2d8bf69');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 67
        }
      ],
      "source": [
        "label = LabelEncoder()\n",
        "balanced_data['label'] = label.fit_transform(balanced_data['activity'])\n",
        "balanced_data"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 68,
      "id": "8175f0cf",
      "metadata": {
        "id": "8175f0cf",
        "outputId": "b756ec3c-2610-456c-92b1-a718d8cb5b03",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['Distracted', 'Drunk', 'Normal'], dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 68
        }
      ],
      "source": [
        "label.classes_"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 69,
      "id": "a37a1fc6",
      "metadata": {
        "id": "a37a1fc6"
      },
      "outputs": [],
      "source": [
        "### Standardised data"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 70,
      "id": "cb5bc432",
      "metadata": {
        "id": "cb5bc432"
      },
      "outputs": [],
      "source": [
        "X = balanced_data[['ax', 'ay', 'az']]\n",
        "y = balanced_data['label']"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 71,
      "id": "e8c03f78",
      "metadata": {
        "id": "e8c03f78",
        "outputId": "b63e2537-52f0-4371-f39d-1efa106205d7",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "             ax        ay        az  label\n",
              "0      0.960997 -0.638312 -0.335892      0\n",
              "1      0.324184 -0.377135 -0.486143      0\n",
              "2      0.264404  0.070210 -0.832611      0\n",
              "3      0.444567 -0.194118 -0.347916      0\n",
              "4     -0.907068  1.202268 -1.206226      0\n",
              "...         ...       ...       ...    ...\n",
              "22791  0.965349  0.157910 -0.200255      2\n",
              "22792  0.967073 -0.428512  0.166284      2\n",
              "22793  1.078177  0.012530 -0.312400      2\n",
              "22794  0.626455  0.722627 -0.365258      2\n",
              "22795 -1.049951  1.378457  0.903801      2\n",
              "\n",
              "[22796 rows x 4 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-cc404144-17e0-4dee-b4fc-3e290e9bd398\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>ax</th>\n",
              "      <th>ay</th>\n",
              "      <th>az</th>\n",
              "      <th>label</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0.960997</td>\n",
              "      <td>-0.638312</td>\n",
              "      <td>-0.335892</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.324184</td>\n",
              "      <td>-0.377135</td>\n",
              "      <td>-0.486143</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.264404</td>\n",
              "      <td>0.070210</td>\n",
              "      <td>-0.832611</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.444567</td>\n",
              "      <td>-0.194118</td>\n",
              "      <td>-0.347916</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>-0.907068</td>\n",
              "      <td>1.202268</td>\n",
              "      <td>-1.206226</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22791</th>\n",
              "      <td>0.965349</td>\n",
              "      <td>0.157910</td>\n",
              "      <td>-0.200255</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22792</th>\n",
              "      <td>0.967073</td>\n",
              "      <td>-0.428512</td>\n",
              "      <td>0.166284</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22793</th>\n",
              "      <td>1.078177</td>\n",
              "      <td>0.012530</td>\n",
              "      <td>-0.312400</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22794</th>\n",
              "      <td>0.626455</td>\n",
              "      <td>0.722627</td>\n",
              "      <td>-0.365258</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22795</th>\n",
              "      <td>-1.049951</td>\n",
              "      <td>1.378457</td>\n",
              "      <td>0.903801</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>22796 rows × 4 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-cc404144-17e0-4dee-b4fc-3e290e9bd398')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-cc404144-17e0-4dee-b4fc-3e290e9bd398 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-cc404144-17e0-4dee-b4fc-3e290e9bd398');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 71
        }
      ],
      "source": [
        "scaler = StandardScaler()\n",
        "X = scaler.fit_transform(X)\n",
        "scaled_X = pd.DataFrame(data = X, columns = ['ax', 'ay', 'az'])\n",
        "scaled_X['label'] = y.values\n",
        "\n",
        "scaled_X"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 72,
      "id": "b9122754",
      "metadata": {
        "id": "b9122754"
      },
      "outputs": [],
      "source": [
        "### Frame Preparation"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 73,
      "id": "841a4a9b",
      "metadata": {
        "id": "841a4a9b"
      },
      "outputs": [],
      "source": [
        "import scipy.stats as stats"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 74,
      "id": "a6696c3b",
      "metadata": {
        "id": "a6696c3b"
      },
      "outputs": [],
      "source": [
        "Fs = 20\n",
        "frame_size = Fs*4\n",
        "hop_size = Fs*2"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 75,
      "id": "ef0dfdef",
      "metadata": {
        "id": "ef0dfdef"
      },
      "outputs": [],
      "source": [
        "def get_frames(df, frame_size, hop_size):\n",
        "    N_FEATURES = 3\n",
        "    frames = []\n",
        "    labels = []\n",
        "    for i in range(0, len(df) - frame_size, hop_size):\n",
        "        x = df['ax'].values[i: i+frame_size]\n",
        "        y = df['ay'].values[i: i+frame_size]\n",
        "        z = df['az'].values[i: i+frame_size]\n",
        "        \n",
        "        label = stats.mode(df['label'][i: i+frame_size])[0][0]\n",
        "        frames.append([x, y, z])\n",
        "        labels.append(label)\n",
        "        \n",
        "    frames = np.asarray(frames).reshape(-1, frame_size, N_FEATURES);\n",
        "    labels = np.asarray(labels)\n",
        "    \n",
        "    return frames, labels"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 76,
      "id": "d760f720",
      "metadata": {
        "id": "d760f720"
      },
      "outputs": [],
      "source": [
        "scaled_X\n",
        "x, y = get_frames(scaled_X, frame_size, hop_size)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 77,
      "id": "e98f6d32",
      "metadata": {
        "id": "e98f6d32",
        "outputId": "83d2d9ec-6bbc-406d-bdd2-67ab8555400e",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "((568, 80, 3), (568,))"
            ]
          },
          "metadata": {},
          "execution_count": 77
        }
      ],
      "source": [
        "x.shape, y.shape"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 78,
      "id": "4fce771c",
      "metadata": {
        "id": "4fce771c"
      },
      "outputs": [],
      "source": [
        "X_train, X_test, y_train, y_test = train_test_split(x, y, test_size = 0.1, random_state = 0, stratify = y)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 79,
      "id": "f9951cea",
      "metadata": {
        "id": "f9951cea",
        "outputId": "62751915-b31b-4256-e1ec-51b15cf9bc1d",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "((511, 80, 3), (57, 80, 3))"
            ]
          },
          "metadata": {},
          "execution_count": 79
        }
      ],
      "source": [
        "X_train.shape, X_test.shape"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 80,
      "id": "ba8d353b",
      "metadata": {
        "id": "ba8d353b"
      },
      "outputs": [],
      "source": [
        "X_train = X_train.reshape(511, 80, 3, 1)\n",
        "X_test = X_test.reshape(57, 80, 3, 1)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 81,
      "id": "7cacf97a",
      "metadata": {
        "id": "7cacf97a",
        "outputId": "cd94943d-33c0-4479-ef83-03f95da24c79",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "((80, 3, 1), (80, 3, 1))"
            ]
          },
          "metadata": {},
          "execution_count": 81
        }
      ],
      "source": [
        "X_train[0].shape, X_test[0].shape"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 82,
      "id": "a3e2818b",
      "metadata": {
        "id": "a3e2818b"
      },
      "outputs": [],
      "source": [
        "model = Sequential()\n",
        "model.add(Conv2D(16, (2, 2), activation = 'relu', input_shape = X_train[0].shape))\n",
        "model.add(Dropout(0.1))\n",
        "model.add(Conv2D(32, (2, 2), activation = 'relu'))\n",
        "model.add(Dropout(0.2))\n",
        "\n",
        "model.add(Flatten())\n",
        "\n",
        "model.add(Dense(64, activation = 'relu'))\n",
        "model.add(Dropout(0.5))\n",
        "model.add(Dense(6, activation = 'softmax'))"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "model.compile(optimizer = Adam(learning_rate = 0.001), loss = 'sparse_categorical_crossentropy', metrics = ['accuracy'])"
      ],
      "metadata": {
        "id": "NIsL3rUM7V92"
      },
      "id": "NIsL3rUM7V92",
      "execution_count": 83,
      "outputs": []
    },
    {
      "cell_type": "code",
      "execution_count": 84,
      "id": "8664233c",
      "metadata": {
        "id": "8664233c",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "221c2b90-f701-43c3-aec8-e7f2757ab9b4"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/20\n",
            "16/16 [==============================] - 1s 21ms/step - loss: 1.3594 - accuracy: 0.3327 - val_loss: 1.0798 - val_accuracy: 0.4912\n",
            "Epoch 2/20\n",
            "16/16 [==============================] - 0s 12ms/step - loss: 1.1117 - accuracy: 0.4188 - val_loss: 1.0067 - val_accuracy: 0.5088\n",
            "Epoch 3/20\n",
            "16/16 [==============================] - 0s 12ms/step - loss: 1.0128 - accuracy: 0.5029 - val_loss: 0.9513 - val_accuracy: 0.5965\n",
            "Epoch 4/20\n",
            "16/16 [==============================] - 0s 12ms/step - loss: 0.8844 - accuracy: 0.6086 - val_loss: 0.9259 - val_accuracy: 0.5614\n",
            "Epoch 5/20\n",
            "16/16 [==============================] - 0s 12ms/step - loss: 0.8268 - accuracy: 0.6869 - val_loss: 0.8850 - val_accuracy: 0.5789\n",
            "Epoch 6/20\n",
            "16/16 [==============================] - 0s 12ms/step - loss: 0.7508 - accuracy: 0.6849 - val_loss: 0.8037 - val_accuracy: 0.6491\n",
            "Epoch 7/20\n",
            "16/16 [==============================] - 0s 12ms/step - loss: 0.6294 - accuracy: 0.7573 - val_loss: 0.8476 - val_accuracy: 0.5614\n",
            "Epoch 8/20\n",
            "16/16 [==============================] - 0s 13ms/step - loss: 0.5803 - accuracy: 0.7828 - val_loss: 0.7618 - val_accuracy: 0.6667\n",
            "Epoch 9/20\n",
            "16/16 [==============================] - 0s 11ms/step - loss: 0.4961 - accuracy: 0.8082 - val_loss: 0.7448 - val_accuracy: 0.6491\n",
            "Epoch 10/20\n",
            "16/16 [==============================] - 0s 16ms/step - loss: 0.4049 - accuracy: 0.8669 - val_loss: 0.7192 - val_accuracy: 0.6842\n",
            "Epoch 11/20\n",
            "16/16 [==============================] - 0s 12ms/step - loss: 0.3918 - accuracy: 0.8513 - val_loss: 0.7436 - val_accuracy: 0.6316\n",
            "Epoch 12/20\n",
            "16/16 [==============================] - 0s 12ms/step - loss: 0.3756 - accuracy: 0.8748 - val_loss: 0.7361 - val_accuracy: 0.6667\n",
            "Epoch 13/20\n",
            "16/16 [==============================] - 0s 13ms/step - loss: 0.3202 - accuracy: 0.8943 - val_loss: 0.7586 - val_accuracy: 0.6842\n",
            "Epoch 14/20\n",
            "16/16 [==============================] - 0s 13ms/step - loss: 0.2996 - accuracy: 0.8924 - val_loss: 0.7716 - val_accuracy: 0.6667\n",
            "Epoch 15/20\n",
            "16/16 [==============================] - 0s 12ms/step - loss: 0.2723 - accuracy: 0.8982 - val_loss: 0.6952 - val_accuracy: 0.6842\n",
            "Epoch 16/20\n",
            "16/16 [==============================] - 0s 11ms/step - loss: 0.2563 - accuracy: 0.9178 - val_loss: 0.6535 - val_accuracy: 0.6842\n",
            "Epoch 17/20\n",
            "16/16 [==============================] - 0s 11ms/step - loss: 0.2250 - accuracy: 0.9335 - val_loss: 0.7386 - val_accuracy: 0.7193\n",
            "Epoch 18/20\n",
            "16/16 [==============================] - 0s 12ms/step - loss: 0.2177 - accuracy: 0.9276 - val_loss: 0.7876 - val_accuracy: 0.6842\n",
            "Epoch 19/20\n",
            "16/16 [==============================] - 0s 11ms/step - loss: 0.2107 - accuracy: 0.9276 - val_loss: 0.7840 - val_accuracy: 0.7018\n",
            "Epoch 20/20\n",
            "16/16 [==============================] - 0s 14ms/step - loss: 0.1884 - accuracy: 0.9354 - val_loss: 0.7738 - val_accuracy: 0.6842\n"
          ]
        }
      ],
      "source": [
        "history = model.fit(X_train, y_train, epochs = 20, validation_data = (X_test, y_test), verbose = 1)"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "converter = tf.lite.TFLiteConverter.from_keras_model(model)\n",
        "tflite_model = converter.convert()"
      ],
      "metadata": {
        "id": "sszLz40bhbw2",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "493a71a5-6957-4642-8675-f5258fdd525a"
      },
      "id": "sszLz40bhbw2",
      "execution_count": 85,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "INFO:tensorflow:Assets written to: /tmp/tmpuqqzalxp/assets\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "INFO:tensorflow:Assets written to: /tmp/tmpuqqzalxp/assets\n",
            "WARNING:absl:Buffer deduplication procedure will be skipped when flatbuffer library is not properly loaded\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1NqPcRvuUzK5",
        "outputId": "2c11fd8d-f0c8-466b-dce3-e1e90d8f2ee8"
      },
      "id": "1NqPcRvuUzK5",
      "execution_count": 86,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ]
    }
  ],
  "metadata": {
    "kernelspec": {
      "display_name": "Python 3 (ipykernel)",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.9.7"
    },
    "colab": {
      "name": "DistractionDetector.ipynb",
      "provenance": [],
      "collapsed_sections": []
    }
  },
  "nbformat": 4,
  "nbformat_minor": 5
}