{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "from os.path import join\n",
    "import sys\n",
    "from pathlib import Path\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "from PIL import Image\n",
    "import cv2 as cv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "fp_attr = '/data_store_hdd/datasets/people/megaface/metadata/face_attributes.csv'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(fp_attr)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "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>index</th>\n",
       "      <th>age_apparent</th>\n",
       "      <th>age_real</th>\n",
       "      <th>f</th>\n",
       "      <th>m</th>\n",
       "      <th>roi_index</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>11.05</td>\n",
       "      <td>18.63</td>\n",
       "      <td>0.8155</td>\n",
       "      <td>0.1845</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>28.59</td>\n",
       "      <td>26.64</td>\n",
       "      <td>0.0219</td>\n",
       "      <td>0.9781</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>12.09</td>\n",
       "      <td>19.08</td>\n",
       "      <td>0.6808</td>\n",
       "      <td>0.3192</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>39.36</td>\n",
       "      <td>51.36</td>\n",
       "      <td>0.9943</td>\n",
       "      <td>0.0057</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>41.84</td>\n",
       "      <td>52.25</td>\n",
       "      <td>0.8226</td>\n",
       "      <td>0.1774</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   index  age_apparent  age_real       f       m  roi_index\n",
       "0      0         11.05     18.63  0.8155  0.1845          0\n",
       "1      1         28.59     26.64  0.0219  0.9781          1\n",
       "2      2         12.09     19.08  0.6808  0.3192          2\n",
       "3      3         39.36     51.36  0.9943  0.0057          3\n",
       "4      4         41.84     52.25  0.8226  0.1774          4"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Less than 21yr: 311,973 (apparent), 168,619 (real)\n",
      "Less than 18yr: 175,628 (apparent), 53,602 (real)\n",
      "Less than 12yr: 35,235 (apparent), 773 (real)\n",
      "Less than 8yr: 1,488 (apparent), 0 (real)\n"
     ]
    }
   ],
   "source": [
    "brackets = [21, 18, 12, 8]\n",
    "for b in brackets:\n",
    "  age_ap = len(df[df['age_apparent'] < b])\n",
    "  age_real = len(df[df['age_real'] < b])\n",
    "  print(f\"Less than {b}yr: {age_ap:,} (apparent), {age_real:,} (real)\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1559780"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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  "kernelspec": {
   "display_name": "megapixels",
   "language": "python",
   "name": "megapixels"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
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