facial-keypoints-detection.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "artificial-spain",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "expired-intelligence",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "D:\\LaureaMagistrale\\Primo_Semestre\\Biometric_Systems\\progetto\\facial-keypoints-detection\\IdLookupTable.csv\n",
      "D:\\LaureaMagistrale\\Primo_Semestre\\Biometric_Systems\\progetto\\facial-keypoints-detection\\SampleSubmission.csv\n",
      "D:\\LaureaMagistrale\\Primo_Semestre\\Biometric_Systems\\progetto\\facial-keypoints-detection\\test\n",
      "D:\\LaureaMagistrale\\Primo_Semestre\\Biometric_Systems\\progetto\\facial-keypoints-detection\\training\n",
      "D:\\LaureaMagistrale\\Primo_Semestre\\Biometric_Systems\\progetto\\facial-keypoints-detection\\test\\test.csv\n",
      "D:\\LaureaMagistrale\\Primo_Semestre\\Biometric_Systems\\progetto\\facial-keypoints-detection\\training\\training.csv\n"
     ]
    }
   ],
   "source": [
    "for root, dirs, files in os.walk('D:\\\\LaureaMagistrale\\\\Primo_Semestre\\\\Biometric_Systems\\\\progetto\\\\facial-keypoints-detection'):\n",
    "    for name in files:\n",
    "        print(os.path.join(root, name))\n",
    "    for name in dirs:\n",
    "        print(os.path.join(root, name))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "boring-proceeding",
   "metadata": {},
   "outputs": [],
   "source": [
    "train_data = pd.read_csv('D:\\\\LaureaMagistrale\\\\Primo_Semestre\\\\Biometric_Systems\\\\progetto\\\\facial-keypoints-detection\\\\training\\\\training.csv', header=0, sep=',', quotechar='\"')\n",
    "test_data = pd.read_csv('D:\\\\LaureaMagistrale\\\\Primo_Semestre\\\\Biometric_Systems\\\\progetto\\\\facial-keypoints-detection\\\\test\\\\test.csv', header=0, sep=',', quotechar='\"')\n",
    "IdLookupTable = pd.read_csv('D:\\\\LaureaMagistrale\\\\Primo_Semestre\\\\Biometric_Systems\\\\progetto\\\\facial-keypoints-detection\\\\IdLookupTable.csv', header=0, sep=',', quotechar='\"')\n",
    "SampleSubmission = pd.read_csv('D:\\\\LaureaMagistrale\\\\Primo_Semestre\\\\Biometric_Systems\\\\progetto\\\\facial-keypoints-detection\\\\SampleSubmission.csv', header=0, sep=',', quotechar='\"')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "driving-piano",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>left_eye_center_x</th>\n",
       "      <th>left_eye_center_y</th>\n",
       "      <th>right_eye_center_x</th>\n",
       "      <th>right_eye_center_y</th>\n",
       "      <th>left_eye_inner_corner_x</th>\n",
       "      <th>left_eye_inner_corner_y</th>\n",
       "      <th>left_eye_outer_corner_x</th>\n",
       "      <th>left_eye_outer_corner_y</th>\n",
       "      <th>right_eye_inner_corner_x</th>\n",
       "      <th>right_eye_inner_corner_y</th>\n",
       "      <th>...</th>\n",
       "      <th>nose_tip_y</th>\n",
       "      <th>mouth_left_corner_x</th>\n",
       "      <th>mouth_left_corner_y</th>\n",
       "      <th>mouth_right_corner_x</th>\n",
       "      <th>mouth_right_corner_y</th>\n",
       "      <th>mouth_center_top_lip_x</th>\n",
       "      <th>mouth_center_top_lip_y</th>\n",
       "      <th>mouth_center_bottom_lip_x</th>\n",
       "      <th>mouth_center_bottom_lip_y</th>\n",
       "      <th>Image</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>66.033564</td>\n",
       "      <td>39.002274</td>\n",
       "      <td>30.227008</td>\n",
       "      <td>36.421678</td>\n",
       "      <td>59.582075</td>\n",
       "      <td>39.647423</td>\n",
       "      <td>73.130346</td>\n",
       "      <td>39.969997</td>\n",
       "      <td>36.356571</td>\n",
       "      <td>37.389402</td>\n",
       "      <td>...</td>\n",
       "      <td>57.066803</td>\n",
       "      <td>61.195308</td>\n",
       "      <td>79.970165</td>\n",
       "      <td>28.614496</td>\n",
       "      <td>77.388992</td>\n",
       "      <td>43.312602</td>\n",
       "      <td>72.935459</td>\n",
       "      <td>43.130707</td>\n",
       "      <td>84.485774</td>\n",
       "      <td>238 236 237 238 240 240 239 241 241 243 240 23...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>64.332936</td>\n",
       "      <td>34.970077</td>\n",
       "      <td>29.949277</td>\n",
       "      <td>33.448715</td>\n",
       "      <td>58.856170</td>\n",
       "      <td>35.274349</td>\n",
       "      <td>70.722723</td>\n",
       "      <td>36.187166</td>\n",
       "      <td>36.034723</td>\n",
       "      <td>34.361532</td>\n",
       "      <td>...</td>\n",
       "      <td>55.660936</td>\n",
       "      <td>56.421447</td>\n",
       "      <td>76.352000</td>\n",
       "      <td>35.122383</td>\n",
       "      <td>76.047660</td>\n",
       "      <td>46.684596</td>\n",
       "      <td>70.266553</td>\n",
       "      <td>45.467915</td>\n",
       "      <td>85.480170</td>\n",
       "      <td>219 215 204 196 204 211 212 200 180 168 178 19...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>65.057053</td>\n",
       "      <td>34.909642</td>\n",
       "      <td>30.903789</td>\n",
       "      <td>34.909642</td>\n",
       "      <td>59.412000</td>\n",
       "      <td>36.320968</td>\n",
       "      <td>70.984421</td>\n",
       "      <td>36.320968</td>\n",
       "      <td>37.678105</td>\n",
       "      <td>36.320968</td>\n",
       "      <td>...</td>\n",
       "      <td>53.538947</td>\n",
       "      <td>60.822947</td>\n",
       "      <td>73.014316</td>\n",
       "      <td>33.726316</td>\n",
       "      <td>72.732000</td>\n",
       "      <td>47.274947</td>\n",
       "      <td>70.191789</td>\n",
       "      <td>47.274947</td>\n",
       "      <td>78.659368</td>\n",
       "      <td>144 142 159 180 188 188 184 180 167 132 84 59 ...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 31 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   left_eye_center_x  left_eye_center_y  right_eye_center_x  \\\n",
       "0          66.033564          39.002274           30.227008   \n",
       "1          64.332936          34.970077           29.949277   \n",
       "2          65.057053          34.909642           30.903789   \n",
       "\n",
       "   right_eye_center_y  left_eye_inner_corner_x  left_eye_inner_corner_y  \\\n",
       "0           36.421678                59.582075                39.647423   \n",
       "1           33.448715                58.856170                35.274349   \n",
       "2           34.909642                59.412000                36.320968   \n",
       "\n",
       "   left_eye_outer_corner_x  left_eye_outer_corner_y  right_eye_inner_corner_x  \\\n",
       "0                73.130346                39.969997                 36.356571   \n",
       "1                70.722723                36.187166                 36.034723   \n",
       "2                70.984421                36.320968                 37.678105   \n",
       "\n",
       "   right_eye_inner_corner_y  ...  nose_tip_y  mouth_left_corner_x  \\\n",
       "0                 37.389402  ...   57.066803            61.195308   \n",
       "1                 34.361532  ...   55.660936            56.421447   \n",
       "2                 36.320968  ...   53.538947            60.822947   \n",
       "\n",
       "   mouth_left_corner_y  mouth_right_corner_x  mouth_right_corner_y  \\\n",
       "0            79.970165             28.614496             77.388992   \n",
       "1            76.352000             35.122383             76.047660   \n",
       "2            73.014316             33.726316             72.732000   \n",
       "\n",
       "   mouth_center_top_lip_x  mouth_center_top_lip_y  mouth_center_bottom_lip_x  \\\n",
       "0               43.312602               72.935459                  43.130707   \n",
       "1               46.684596               70.266553                  45.467915   \n",
       "2               47.274947               70.191789                  47.274947   \n",
       "\n",
       "   mouth_center_bottom_lip_y  \\\n",
       "0                  84.485774   \n",
       "1                  85.480170   \n",
       "2                  78.659368   \n",
       "\n",
       "                                               Image  \n",
       "0  238 236 237 238 240 240 239 241 241 243 240 23...  \n",
       "1  219 215 204 196 204 211 212 200 180 168 178 19...  \n",
       "2  144 142 159 180 188 188 184 180 167 132 84 59 ...  \n",
       "\n",
       "[3 rows x 31 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_data.head(3)\n",
    "# each row an image\n",
    "# the cells define the real-values position in term of pixels indexes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "critical-condition",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>left_eye_center_x</th>\n",
       "      <th>left_eye_center_y</th>\n",
       "      <th>right_eye_center_x</th>\n",
       "      <th>right_eye_center_y</th>\n",
       "      <th>left_eye_inner_corner_x</th>\n",
       "      <th>left_eye_inner_corner_y</th>\n",
       "      <th>left_eye_outer_corner_x</th>\n",
       "      <th>left_eye_outer_corner_y</th>\n",
       "      <th>right_eye_inner_corner_x</th>\n",
       "      <th>right_eye_inner_corner_y</th>\n",
       "      <th>...</th>\n",
       "      <th>nose_tip_x</th>\n",
       "      <th>nose_tip_y</th>\n",
       "      <th>mouth_left_corner_x</th>\n",
       "      <th>mouth_left_corner_y</th>\n",
       "      <th>mouth_right_corner_x</th>\n",
       "      <th>mouth_right_corner_y</th>\n",
       "      <th>mouth_center_top_lip_x</th>\n",
       "      <th>mouth_center_top_lip_y</th>\n",
       "      <th>mouth_center_bottom_lip_x</th>\n",
       "      <th>mouth_center_bottom_lip_y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>7039.000000</td>\n",
       "      <td>7039.000000</td>\n",
       "      <td>7036.000000</td>\n",
       "      <td>7036.000000</td>\n",
       "      <td>2271.000000</td>\n",
       "      <td>2271.000000</td>\n",
       "      <td>2267.000000</td>\n",
       "      <td>2267.000000</td>\n",
       "      <td>2268.000000</td>\n",
       "      <td>2268.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>7049.000000</td>\n",
       "      <td>7049.000000</td>\n",
       "      <td>2269.000000</td>\n",
       "      <td>2269.000000</td>\n",
       "      <td>2270.000000</td>\n",
       "      <td>2270.000000</td>\n",
       "      <td>2275.000000</td>\n",
       "      <td>2275.000000</td>\n",
       "      <td>7016.000000</td>\n",
       "      <td>7016.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>66.359021</td>\n",
       "      <td>37.651234</td>\n",
       "      <td>30.306102</td>\n",
       "      <td>37.976943</td>\n",
       "      <td>59.159339</td>\n",
       "      <td>37.944752</td>\n",
       "      <td>73.330478</td>\n",
       "      <td>37.707008</td>\n",
       "      <td>36.652607</td>\n",
       "      <td>37.989902</td>\n",
       "      <td>...</td>\n",
       "      <td>48.374186</td>\n",
       "      <td>62.715884</td>\n",
       "      <td>63.285735</td>\n",
       "      <td>75.970714</td>\n",
       "      <td>32.900404</td>\n",
       "      <td>76.179768</td>\n",
       "      <td>47.975412</td>\n",
       "      <td>72.919443</td>\n",
       "      <td>48.569472</td>\n",
       "      <td>78.970146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>3.448233</td>\n",
       "      <td>3.152926</td>\n",
       "      <td>3.083230</td>\n",
       "      <td>3.033621</td>\n",
       "      <td>2.690354</td>\n",
       "      <td>2.307332</td>\n",
       "      <td>3.405852</td>\n",
       "      <td>2.881438</td>\n",
       "      <td>2.350268</td>\n",
       "      <td>2.311907</td>\n",
       "      <td>...</td>\n",
       "      <td>4.280038</td>\n",
       "      <td>5.720567</td>\n",
       "      <td>4.079063</td>\n",
       "      <td>4.579724</td>\n",
       "      <td>3.964552</td>\n",
       "      <td>4.417814</td>\n",
       "      <td>3.323060</td>\n",
       "      <td>5.222500</td>\n",
       "      <td>4.269961</td>\n",
       "      <td>5.407844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>22.763345</td>\n",
       "      <td>1.616512</td>\n",
       "      <td>0.686592</td>\n",
       "      <td>4.091264</td>\n",
       "      <td>19.064954</td>\n",
       "      <td>27.190098</td>\n",
       "      <td>27.571879</td>\n",
       "      <td>26.250023</td>\n",
       "      <td>5.751046</td>\n",
       "      <td>26.250023</td>\n",
       "      <td>...</td>\n",
       "      <td>12.944699</td>\n",
       "      <td>17.932414</td>\n",
       "      <td>22.923362</td>\n",
       "      <td>57.023258</td>\n",
       "      <td>2.245766</td>\n",
       "      <td>56.690208</td>\n",
       "      <td>12.605173</td>\n",
       "      <td>56.719043</td>\n",
       "      <td>12.536477</td>\n",
       "      <td>25.850503</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>65.082895</td>\n",
       "      <td>35.900451</td>\n",
       "      <td>28.783339</td>\n",
       "      <td>36.327681</td>\n",
       "      <td>58.039339</td>\n",
       "      <td>36.626283</td>\n",
       "      <td>71.716503</td>\n",
       "      <td>36.085523</td>\n",
       "      <td>35.506126</td>\n",
       "      <td>36.766783</td>\n",
       "      <td>...</td>\n",
       "      <td>46.602370</td>\n",
       "      <td>59.292697</td>\n",
       "      <td>61.257143</td>\n",
       "      <td>72.875707</td>\n",
       "      <td>30.797646</td>\n",
       "      <td>73.256472</td>\n",
       "      <td>46.494571</td>\n",
       "      <td>69.396748</td>\n",
       "      <td>46.573703</td>\n",
       "      <td>75.549715</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>66.497566</td>\n",
       "      <td>37.528055</td>\n",
       "      <td>30.251378</td>\n",
       "      <td>37.813273</td>\n",
       "      <td>59.304615</td>\n",
       "      <td>37.878040</td>\n",
       "      <td>73.247824</td>\n",
       "      <td>37.639015</td>\n",
       "      <td>36.651562</td>\n",
       "      <td>37.944075</td>\n",
       "      <td>...</td>\n",
       "      <td>48.424713</td>\n",
       "      <td>63.451421</td>\n",
       "      <td>63.178286</td>\n",
       "      <td>75.778689</td>\n",
       "      <td>32.982305</td>\n",
       "      <td>76.000592</td>\n",
       "      <td>47.905490</td>\n",
       "      <td>72.605173</td>\n",
       "      <td>48.594978</td>\n",
       "      <td>78.696326</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>68.024752</td>\n",
       "      <td>39.258449</td>\n",
       "      <td>31.768334</td>\n",
       "      <td>39.566729</td>\n",
       "      <td>60.519810</td>\n",
       "      <td>39.260348</td>\n",
       "      <td>75.015645</td>\n",
       "      <td>39.373489</td>\n",
       "      <td>37.753571</td>\n",
       "      <td>39.192917</td>\n",
       "      <td>...</td>\n",
       "      <td>50.330437</td>\n",
       "      <td>66.492686</td>\n",
       "      <td>65.376243</td>\n",
       "      <td>78.879123</td>\n",
       "      <td>35.101302</td>\n",
       "      <td>78.956357</td>\n",
       "      <td>49.296488</td>\n",
       "      <td>76.221644</td>\n",
       "      <td>50.677631</td>\n",
       "      <td>82.233993</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>94.689280</td>\n",
       "      <td>80.502649</td>\n",
       "      <td>85.039381</td>\n",
       "      <td>81.270911</td>\n",
       "      <td>84.440991</td>\n",
       "      <td>66.562559</td>\n",
       "      <td>95.258090</td>\n",
       "      <td>64.618230</td>\n",
       "      <td>70.714966</td>\n",
       "      <td>69.808803</td>\n",
       "      <td>...</td>\n",
       "      <td>89.438592</td>\n",
       "      <td>95.935644</td>\n",
       "      <td>84.767123</td>\n",
       "      <td>94.673637</td>\n",
       "      <td>74.017993</td>\n",
       "      <td>95.510678</td>\n",
       "      <td>83.989082</td>\n",
       "      <td>94.548359</td>\n",
       "      <td>89.438592</td>\n",
       "      <td>95.808983</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       left_eye_center_x  left_eye_center_y  right_eye_center_x  \\\n",
       "count        7039.000000        7039.000000         7036.000000   \n",
       "mean           66.359021          37.651234           30.306102   \n",
       "std             3.448233           3.152926            3.083230   \n",
       "min            22.763345           1.616512            0.686592   \n",
       "25%            65.082895          35.900451           28.783339   \n",
       "50%            66.497566          37.528055           30.251378   \n",
       "75%            68.024752          39.258449           31.768334   \n",
       "max            94.689280          80.502649           85.039381   \n",
       "\n",
       "       right_eye_center_y  left_eye_inner_corner_x  left_eye_inner_corner_y  \\\n",
       "count         7036.000000              2271.000000              2271.000000   \n",
       "mean            37.976943                59.159339                37.944752   \n",
       "std              3.033621                 2.690354                 2.307332   \n",
       "min              4.091264                19.064954                27.190098   \n",
       "25%             36.327681                58.039339                36.626283   \n",
       "50%             37.813273                59.304615                37.878040   \n",
       "75%             39.566729                60.519810                39.260348   \n",
       "max             81.270911                84.440991                66.562559   \n",
       "\n",
       "       left_eye_outer_corner_x  left_eye_outer_corner_y  \\\n",
       "count              2267.000000              2267.000000   \n",
       "mean                 73.330478                37.707008   \n",
       "std                   3.405852                 2.881438   \n",
       "min                  27.571879                26.250023   \n",
       "25%                  71.716503                36.085523   \n",
       "50%                  73.247824                37.639015   \n",
       "75%                  75.015645                39.373489   \n",
       "max                  95.258090                64.618230   \n",
       "\n",
       "       right_eye_inner_corner_x  right_eye_inner_corner_y  ...   nose_tip_x  \\\n",
       "count               2268.000000               2268.000000  ...  7049.000000   \n",
       "mean                  36.652607                 37.989902  ...    48.374186   \n",
       "std                    2.350268                  2.311907  ...     4.280038   \n",
       "min                    5.751046                 26.250023  ...    12.944699   \n",
       "25%                   35.506126                 36.766783  ...    46.602370   \n",
       "50%                   36.651562                 37.944075  ...    48.424713   \n",
       "75%                   37.753571                 39.192917  ...    50.330437   \n",
       "max                   70.714966                 69.808803  ...    89.438592   \n",
       "\n",
       "        nose_tip_y  mouth_left_corner_x  mouth_left_corner_y  \\\n",
       "count  7049.000000          2269.000000          2269.000000   \n",
       "mean     62.715884            63.285735            75.970714   \n",
       "std       5.720567             4.079063             4.579724   \n",
       "min      17.932414            22.923362            57.023258   \n",
       "25%      59.292697            61.257143            72.875707   \n",
       "50%      63.451421            63.178286            75.778689   \n",
       "75%      66.492686            65.376243            78.879123   \n",
       "max      95.935644            84.767123            94.673637   \n",
       "\n",
       "       mouth_right_corner_x  mouth_right_corner_y  mouth_center_top_lip_x  \\\n",
       "count           2270.000000           2270.000000             2275.000000   \n",
       "mean              32.900404             76.179768               47.975412   \n",
       "std                3.964552              4.417814                3.323060   \n",
       "min                2.245766             56.690208               12.605173   \n",
       "25%               30.797646             73.256472               46.494571   \n",
       "50%               32.982305             76.000592               47.905490   \n",
       "75%               35.101302             78.956357               49.296488   \n",
       "max               74.017993             95.510678               83.989082   \n",
       "\n",
       "       mouth_center_top_lip_y  mouth_center_bottom_lip_x  \\\n",
       "count             2275.000000                7016.000000   \n",
       "mean                72.919443                  48.569472   \n",
       "std                  5.222500                   4.269961   \n",
       "min                 56.719043                  12.536477   \n",
       "25%                 69.396748                  46.573703   \n",
       "50%                 72.605173                  48.594978   \n",
       "75%                 76.221644                  50.677631   \n",
       "max                 94.548359                  89.438592   \n",
       "\n",
       "       mouth_center_bottom_lip_y  \n",
       "count                7016.000000  \n",
       "mean                   78.970146  \n",
       "std                     5.407844  \n",
       "min                    25.850503  \n",
       "25%                    75.549715  \n",
       "50%                    78.696326  \n",
       "75%                    82.233993  \n",
       "max                    95.808983  \n",
       "\n",
       "[8 rows x 30 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_data.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "focal-parent",
   "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>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>...</th>\n",
       "      <th>7039</th>\n",
       "      <th>7040</th>\n",
       "      <th>7041</th>\n",
       "      <th>7042</th>\n",
       "      <th>7043</th>\n",
       "      <th>7044</th>\n",
       "      <th>7045</th>\n",
       "      <th>7046</th>\n",
       "      <th>7047</th>\n",
       "      <th>7048</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>mouth_center_top_lip_x</th>\n",
       "      <td>43.3126</td>\n",
       "      <td>46.6846</td>\n",
       "      <td>47.2749</td>\n",
       "      <td>50.3032</td>\n",
       "      <td>44.9627</td>\n",
       "      <td>49.3081</td>\n",
       "      <td>45.1277</td>\n",
       "      <td>48.1002</td>\n",
       "      <td>49.2134</td>\n",
       "      <td>49.2702</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mouth_center_top_lip_y</th>\n",
       "      <td>72.9355</td>\n",
       "      <td>70.2666</td>\n",
       "      <td>70.1918</td>\n",
       "      <td>70.0917</td>\n",
       "      <td>73.7074</td>\n",
       "      <td>78.4876</td>\n",
       "      <td>65.0996</td>\n",
       "      <td>71.2786</td>\n",
       "      <td>67.648</td>\n",
       "      <td>67.5428</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mouth_center_bottom_lip_x</th>\n",
       "      <td>43.1307</td>\n",
       "      <td>45.4679</td>\n",
       "      <td>47.2749</td>\n",
       "      <td>51.5612</td>\n",
       "      <td>44.2271</td>\n",
       "      <td>49.4324</td>\n",
       "      <td>45.4157</td>\n",
       "      <td>48.5168</td>\n",
       "      <td>49.4995</td>\n",
       "      <td>49.5452</td>\n",
       "      <td>...</td>\n",
       "      <td>50.1245</td>\n",
       "      <td>50.3676</td>\n",
       "      <td>49.7862</td>\n",
       "      <td>52.4463</td>\n",
       "      <td>47.555</td>\n",
       "      <td>50.4266</td>\n",
       "      <td>50.2874</td>\n",
       "      <td>49.4626</td>\n",
       "      <td>50.0652</td>\n",
       "      <td>45.9005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mouth_center_bottom_lip_y</th>\n",
       "      <td>84.4858</td>\n",
       "      <td>85.4802</td>\n",
       "      <td>78.6594</td>\n",
       "      <td>78.2684</td>\n",
       "      <td>86.8712</td>\n",
       "      <td>93.8988</td>\n",
       "      <td>78.057</td>\n",
       "      <td>91.0639</td>\n",
       "      <td>83.0931</td>\n",
       "      <td>76.8935</td>\n",
       "      <td>...</td>\n",
       "      <td>80.2391</td>\n",
       "      <td>70.9523</td>\n",
       "      <td>78.2009</td>\n",
       "      <td>81.2278</td>\n",
       "      <td>79.4926</td>\n",
       "      <td>79.6839</td>\n",
       "      <td>77.983</td>\n",
       "      <td>78.1171</td>\n",
       "      <td>79.5864</td>\n",
       "      <td>82.7731</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Image</th>\n",
       "      <td>238 236 237 238 240 240 239 241 241 243 240 23...</td>\n",
       "      <td>219 215 204 196 204 211 212 200 180 168 178 19...</td>\n",
       "      <td>144 142 159 180 188 188 184 180 167 132 84 59 ...</td>\n",
       "      <td>193 192 193 194 194 194 193 192 168 111 50 12 ...</td>\n",
       "      <td>147 148 160 196 215 214 216 217 219 220 206 18...</td>\n",
       "      <td>167 169 170 167 156 145 106 68 52 24 20 15 21 ...</td>\n",
       "      <td>109 109 125 141 145 139 120 81 45 34 31 35 36 ...</td>\n",
       "      <td>178 177 178 179 179 179 181 185 188 184 192 20...</td>\n",
       "      <td>164 158 118 76 66 69 59 53 43 31 35 41 45 55 6...</td>\n",
       "      <td>226 227 225 224 221 220 215 210 210 208 206 18...</td>\n",
       "      <td>...</td>\n",
       "      <td>43 49 57 67 81 98 97 94 91 94 97 101 96 91 88 ...</td>\n",
       "      <td>139 140 143 141 141 140 140 139 140 141 143 14...</td>\n",
       "      <td>164 165 167 168 169 170 172 171 170 171 173 16...</td>\n",
       "      <td>254 235 191 141 106 93 94 123 168 178 178 186 ...</td>\n",
       "      <td>150 150 132 63 44 74 86 61 62 57 44 70 93 115 ...</td>\n",
       "      <td>71 74 85 105 116 128 139 150 170 187 201 209 2...</td>\n",
       "      <td>60 60 62 57 55 51 49 48 50 53 56 56 106 89 77 ...</td>\n",
       "      <td>74 74 74 78 79 79 79 81 77 78 80 73 72 81 77 1...</td>\n",
       "      <td>254 254 254 254 254 238 193 145 121 118 119 10...</td>\n",
       "      <td>53 62 67 76 86 91 97 105 105 106 107 108 112 1...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 7049 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                                        0     \\\n",
       "mouth_center_top_lip_x                                               43.3126   \n",
       "mouth_center_top_lip_y                                               72.9355   \n",
       "mouth_center_bottom_lip_x                                            43.1307   \n",
       "mouth_center_bottom_lip_y                                            84.4858   \n",
       "Image                      238 236 237 238 240 240 239 241 241 243 240 23...   \n",
       "\n",
       "                                                                        1     \\\n",
       "mouth_center_top_lip_x                                               46.6846   \n",
       "mouth_center_top_lip_y                                               70.2666   \n",
       "mouth_center_bottom_lip_x                                            45.4679   \n",
       "mouth_center_bottom_lip_y                                            85.4802   \n",
       "Image                      219 215 204 196 204 211 212 200 180 168 178 19...   \n",
       "\n",
       "                                                                        2     \\\n",
       "mouth_center_top_lip_x                                               47.2749   \n",
       "mouth_center_top_lip_y                                               70.1918   \n",
       "mouth_center_bottom_lip_x                                            47.2749   \n",
       "mouth_center_bottom_lip_y                                            78.6594   \n",
       "Image                      144 142 159 180 188 188 184 180 167 132 84 59 ...   \n",
       "\n",
       "                                                                        3     \\\n",
       "mouth_center_top_lip_x                                               50.3032   \n",
       "mouth_center_top_lip_y                                               70.0917   \n",
       "mouth_center_bottom_lip_x                                            51.5612   \n",
       "mouth_center_bottom_lip_y                                            78.2684   \n",
       "Image                      193 192 193 194 194 194 193 192 168 111 50 12 ...   \n",
       "\n",
       "                                                                        4     \\\n",
       "mouth_center_top_lip_x                                               44.9627   \n",
       "mouth_center_top_lip_y                                               73.7074   \n",
       "mouth_center_bottom_lip_x                                            44.2271   \n",
       "mouth_center_bottom_lip_y                                            86.8712   \n",
       "Image                      147 148 160 196 215 214 216 217 219 220 206 18...   \n",
       "\n",
       "                                                                        5     \\\n",
       "mouth_center_top_lip_x                                               49.3081   \n",
       "mouth_center_top_lip_y                                               78.4876   \n",
       "mouth_center_bottom_lip_x                                            49.4324   \n",
       "mouth_center_bottom_lip_y                                            93.8988   \n",
       "Image                      167 169 170 167 156 145 106 68 52 24 20 15 21 ...   \n",
       "\n",
       "                                                                        6     \\\n",
       "mouth_center_top_lip_x                                               45.1277   \n",
       "mouth_center_top_lip_y                                               65.0996   \n",
       "mouth_center_bottom_lip_x                                            45.4157   \n",
       "mouth_center_bottom_lip_y                                             78.057   \n",
       "Image                      109 109 125 141 145 139 120 81 45 34 31 35 36 ...   \n",
       "\n",
       "                                                                        7     \\\n",
       "mouth_center_top_lip_x                                               48.1002   \n",
       "mouth_center_top_lip_y                                               71.2786   \n",
       "mouth_center_bottom_lip_x                                            48.5168   \n",
       "mouth_center_bottom_lip_y                                            91.0639   \n",
       "Image                      178 177 178 179 179 179 181 185 188 184 192 20...   \n",
       "\n",
       "                                                                        8     \\\n",
       "mouth_center_top_lip_x                                               49.2134   \n",
       "mouth_center_top_lip_y                                                67.648   \n",
       "mouth_center_bottom_lip_x                                            49.4995   \n",
       "mouth_center_bottom_lip_y                                            83.0931   \n",
       "Image                      164 158 118 76 66 69 59 53 43 31 35 41 45 55 6...   \n",
       "\n",
       "                                                                        9     \\\n",
       "mouth_center_top_lip_x                                               49.2702   \n",
       "mouth_center_top_lip_y                                               67.5428   \n",
       "mouth_center_bottom_lip_x                                            49.5452   \n",
       "mouth_center_bottom_lip_y                                            76.8935   \n",
       "Image                      226 227 225 224 221 220 215 210 210 208 206 18...   \n",
       "\n",
       "                           ...  \\\n",
       "mouth_center_top_lip_x     ...   \n",
       "mouth_center_top_lip_y     ...   \n",
       "mouth_center_bottom_lip_x  ...   \n",
       "mouth_center_bottom_lip_y  ...   \n",
       "Image                      ...   \n",
       "\n",
       "                                                                        7039  \\\n",
       "mouth_center_top_lip_x                                                   NaN   \n",
       "mouth_center_top_lip_y                                                   NaN   \n",
       "mouth_center_bottom_lip_x                                            50.1245   \n",
       "mouth_center_bottom_lip_y                                            80.2391   \n",
       "Image                      43 49 57 67 81 98 97 94 91 94 97 101 96 91 88 ...   \n",
       "\n",
       "                                                                        7040  \\\n",
       "mouth_center_top_lip_x                                                   NaN   \n",
       "mouth_center_top_lip_y                                                   NaN   \n",
       "mouth_center_bottom_lip_x                                            50.3676   \n",
       "mouth_center_bottom_lip_y                                            70.9523   \n",
       "Image                      139 140 143 141 141 140 140 139 140 141 143 14...   \n",
       "\n",
       "                                                                        7041  \\\n",
       "mouth_center_top_lip_x                                                   NaN   \n",
       "mouth_center_top_lip_y                                                   NaN   \n",
       "mouth_center_bottom_lip_x                                            49.7862   \n",
       "mouth_center_bottom_lip_y                                            78.2009   \n",
       "Image                      164 165 167 168 169 170 172 171 170 171 173 16...   \n",
       "\n",
       "                                                                        7042  \\\n",
       "mouth_center_top_lip_x                                                   NaN   \n",
       "mouth_center_top_lip_y                                                   NaN   \n",
       "mouth_center_bottom_lip_x                                            52.4463   \n",
       "mouth_center_bottom_lip_y                                            81.2278   \n",
       "Image                      254 235 191 141 106 93 94 123 168 178 178 186 ...   \n",
       "\n",
       "                                                                        7043  \\\n",
       "mouth_center_top_lip_x                                                   NaN   \n",
       "mouth_center_top_lip_y                                                   NaN   \n",
       "mouth_center_bottom_lip_x                                             47.555   \n",
       "mouth_center_bottom_lip_y                                            79.4926   \n",
       "Image                      150 150 132 63 44 74 86 61 62 57 44 70 93 115 ...   \n",
       "\n",
       "                                                                        7044  \\\n",
       "mouth_center_top_lip_x                                                   NaN   \n",
       "mouth_center_top_lip_y                                                   NaN   \n",
       "mouth_center_bottom_lip_x                                            50.4266   \n",
       "mouth_center_bottom_lip_y                                            79.6839   \n",
       "Image                      71 74 85 105 116 128 139 150 170 187 201 209 2...   \n",
       "\n",
       "                                                                        7045  \\\n",
       "mouth_center_top_lip_x                                                   NaN   \n",
       "mouth_center_top_lip_y                                                   NaN   \n",
       "mouth_center_bottom_lip_x                                            50.2874   \n",
       "mouth_center_bottom_lip_y                                             77.983   \n",
       "Image                      60 60 62 57 55 51 49 48 50 53 56 56 106 89 77 ...   \n",
       "\n",
       "                                                                        7046  \\\n",
       "mouth_center_top_lip_x                                                   NaN   \n",
       "mouth_center_top_lip_y                                                   NaN   \n",
       "mouth_center_bottom_lip_x                                            49.4626   \n",
       "mouth_center_bottom_lip_y                                            78.1171   \n",
       "Image                      74 74 74 78 79 79 79 81 77 78 80 73 72 81 77 1...   \n",
       "\n",
       "                                                                        7047  \\\n",
       "mouth_center_top_lip_x                                                   NaN   \n",
       "mouth_center_top_lip_y                                                   NaN   \n",
       "mouth_center_bottom_lip_x                                            50.0652   \n",
       "mouth_center_bottom_lip_y                                            79.5864   \n",
       "Image                      254 254 254 254 254 238 193 145 121 118 119 10...   \n",
       "\n",
       "                                                                        7048  \n",
       "mouth_center_top_lip_x                                                   NaN  \n",
       "mouth_center_top_lip_y                                                   NaN  \n",
       "mouth_center_bottom_lip_x                                            45.9005  \n",
       "mouth_center_bottom_lip_y                                            82.7731  \n",
       "Image                      53 62 67 76 86 91 97 105 105 106 107 108 112 1...  \n",
       "\n",
       "[5 rows x 7049 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_data.T.tail() # just focus on how images are stored"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "personalized-teach",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Il lato dell'immagine 0 è: 96\n",
      "Il lato dell'immagine 1 è: 96\n",
      "Il lato dell'immagine 2 è: 96\n",
      "Il lato dell'immagine 3 è: 96\n",
      "Il lato dell'immagine 4 è: 96\n",
      "Il lato dell'immagine 5 è: 96\n",
      "Il lato dell'immagine 6 è: 96\n",
      "Il lato dell'immagine 7 è: 96\n",
      "Il lato dell'immagine 8 è: 96\n",
      "Il lato dell'immagine 9 è: 96\n"
     ]
    }
   ],
   "source": [
    "for ix in range(10):\n",
    "    imgString = train_data['Image'][ix] # it is a string object\n",
    "    nPixels = len(imgString.split())\n",
    "    imgDim = np.sqrt(nPixels).astype(int) # numero pixel per lato\n",
    "    print(\"Il lato dell'immagine {} è: {}\".format(ix,imgDim))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "naked-steering",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 7049 entries, 0 to 7048\n",
      "Data columns (total 31 columns):\n",
      " #   Column                     Non-Null Count  Dtype  \n",
      "---  ------                     --------------  -----  \n",
      " 0   left_eye_center_x          7039 non-null   float64\n",
      " 1   left_eye_center_y          7039 non-null   float64\n",
      " 2   right_eye_center_x         7036 non-null   float64\n",
      " 3   right_eye_center_y         7036 non-null   float64\n",
      " 4   left_eye_inner_corner_x    2271 non-null   float64\n",
      " 5   left_eye_inner_corner_y    2271 non-null   float64\n",
      " 6   left_eye_outer_corner_x    2267 non-null   float64\n",
      " 7   left_eye_outer_corner_y    2267 non-null   float64\n",
      " 8   right_eye_inner_corner_x   2268 non-null   float64\n",
      " 9   right_eye_inner_corner_y   2268 non-null   float64\n",
      " 10  right_eye_outer_corner_x   2268 non-null   float64\n",
      " 11  right_eye_outer_corner_y   2268 non-null   float64\n",
      " 12  left_eyebrow_inner_end_x   2270 non-null   float64\n",
      " 13  left_eyebrow_inner_end_y   2270 non-null   float64\n",
      " 14  left_eyebrow_outer_end_x   2225 non-null   float64\n",
      " 15  left_eyebrow_outer_end_y   2225 non-null   float64\n",
      " 16  right_eyebrow_inner_end_x  2270 non-null   float64\n",
      " 17  right_eyebrow_inner_end_y  2270 non-null   float64\n",
      " 18  right_eyebrow_outer_end_x  2236 non-null   float64\n",
      " 19  right_eyebrow_outer_end_y  2236 non-null   float64\n",
      " 20  nose_tip_x                 7049 non-null   float64\n",
      " 21  nose_tip_y                 7049 non-null   float64\n",
      " 22  mouth_left_corner_x        2269 non-null   float64\n",
      " 23  mouth_left_corner_y        2269 non-null   float64\n",
      " 24  mouth_right_corner_x       2270 non-null   float64\n",
      " 25  mouth_right_corner_y       2270 non-null   float64\n",
      " 26  mouth_center_top_lip_x     2275 non-null   float64\n",
      " 27  mouth_center_top_lip_y     2275 non-null   float64\n",
      " 28  mouth_center_bottom_lip_x  7016 non-null   float64\n",
      " 29  mouth_center_bottom_lip_y  7016 non-null   float64\n",
      " 30  Image                      7049 non-null   object \n",
      "dtypes: float64(30), object(1)\n",
      "memory usage: 1.7+ MB\n"
     ]
    }
   ],
   "source": [
    "train_data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "geographic-spectrum",
   "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>ImageId</th>\n",
       "      <th>Image</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>182 183 182 182 180 180 176 169 156 137 124 10...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>76 87 81 72 65 59 64 76 69 42 31 38 49 58 58 4...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>177 176 174 170 169 169 168 166 166 166 161 14...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>176 174 174 175 174 174 176 176 175 171 165 15...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>50 47 44 101 144 149 120 58 48 42 35 35 37 39 ...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ImageId                                              Image\n",
       "0        1  182 183 182 182 180 180 176 169 156 137 124 10...\n",
       "1        2  76 87 81 72 65 59 64 76 69 42 31 38 49 58 58 4...\n",
       "2        3  177 176 174 170 169 169 168 166 166 166 161 14...\n",
       "3        4  176 174 174 175 174 174 176 176 175 171 165 15...\n",
       "4        5  50 47 44 101 144 149 120 58 48 42 35 35 37 39 ..."
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "blind-excitement",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1783 entries, 0 to 1782\n",
      "Data columns (total 2 columns):\n",
      " #   Column   Non-Null Count  Dtype \n",
      "---  ------   --------------  ----- \n",
      " 0   ImageId  1783 non-null   int64 \n",
      " 1   Image    1783 non-null   object\n",
      "dtypes: int64(1), object(1)\n",
      "memory usage: 28.0+ KB\n"
     ]
    }
   ],
   "source": [
    "test_data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "equal-november",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Il lato dell'immagine 0 è: 96\n",
      "Il lato dell'immagine 1 è: 96\n",
      "Il lato dell'immagine 2 è: 96\n",
      "Il lato dell'immagine 3 è: 96\n",
      "Il lato dell'immagine 4 è: 96\n",
      "Il lato dell'immagine 5 è: 96\n",
      "Il lato dell'immagine 6 è: 96\n",
      "Il lato dell'immagine 7 è: 96\n",
      "Il lato dell'immagine 8 è: 96\n",
      "Il lato dell'immagine 9 è: 96\n"
     ]
    }
   ],
   "source": [
    "for ix in range(10):\n",
    "    imgString = test_data['Image'][ix] # it is a string object\n",
    "    nPixels = len(imgString.split())\n",
    "    imgDim = np.sqrt(nPixels).astype(int) # numero pixel per lato\n",
    "    print(\"Il lato dell'immagine {} è: {}\".format(ix,imgDim))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "pleased-calvin",
   "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>RowId</th>\n",
       "      <th>ImageId</th>\n",
       "      <th>FeatureName</th>\n",
       "      <th>Location</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>left_eye_center_x</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>left_eye_center_y</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>right_eye_center_x</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>right_eye_center_y</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>left_eye_inner_corner_x</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   RowId  ImageId              FeatureName  Location\n",
       "0      1        1        left_eye_center_x       NaN\n",
       "1      2        1        left_eye_center_y       NaN\n",
       "2      3        1       right_eye_center_x       NaN\n",
       "3      4        1       right_eye_center_y       NaN\n",
       "4      5        1  left_eye_inner_corner_x       NaN"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "IdLookupTable.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "adolescent-conditioning",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 27124 entries, 0 to 27123\n",
      "Data columns (total 4 columns):\n",
      " #   Column       Non-Null Count  Dtype  \n",
      "---  ------       --------------  -----  \n",
      " 0   RowId        27124 non-null  int64  \n",
      " 1   ImageId      27124 non-null  int64  \n",
      " 2   FeatureName  27124 non-null  object \n",
      " 3   Location     0 non-null      float64\n",
      "dtypes: float64(1), int64(2), object(1)\n",
      "memory usage: 847.8+ KB\n"
     ]
    }
   ],
   "source": [
    "IdLookupTable.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "subsequent-section",
   "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>RowId</th>\n",
       "      <th>Location</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   RowId  Location\n",
       "0      1         0\n",
       "1      2         0\n",
       "2      3         0\n",
       "3      4         0\n",
       "4      5         0"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "SampleSubmission.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "illegal-british",
   "metadata": {},
   "source": [
    "### Check Missing Data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "closed-wichita",
   "metadata": {},
   "source": [
    "#### Train Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "large-saver",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([  10,   10,   13,   13, 4778, 4778, 4782, 4782, 4781, 4781, 4781,\n",
       "       4781, 4779, 4779, 4824, 4824, 4779, 4779, 4813, 4813,    0,    0,\n",
       "       4780, 4780, 4779, 4779, 4774, 4774,   33,   33,    0], dtype=int64)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_data.isnull().sum().values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "numerical-cardiff",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 2160x1440 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(30,20))\n",
    "fig = sns.barplot(x = train_data.isnull().sum().values, y = train_data.isnull().sum().index)\n",
    "fig.tick_params(labelsize=22)\n",
    "plt.xlabel(\"Count\", fontsize=30)\n",
    "plt.ylabel(\"Location\", fontsize=30)\n",
    "plt.title(\"Missing Data of POI location - Train set\", fontsize=30)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "identical-crossing",
   "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>left_eye_inner_corner_x</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>59.582075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>58.856170</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>59.412000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>60.003339</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>58.565890</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7044</th>\n",
       "      <td>59.255347</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7045</th>\n",
       "      <td>59.255347</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7046</th>\n",
       "      <td>59.255347</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7047</th>\n",
       "      <td>59.255347</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7048</th>\n",
       "      <td>59.255347</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7049 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      left_eye_inner_corner_x\n",
       "0                   59.582075\n",
       "1                   58.856170\n",
       "2                   59.412000\n",
       "3                   60.003339\n",
       "4                   58.565890\n",
       "...                       ...\n",
       "7044                59.255347\n",
       "7045                59.255347\n",
       "7046                59.255347\n",
       "7047                59.255347\n",
       "7048                59.255347\n",
       "\n",
       "[7049 rows x 1 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_data.fillna(method = 'ffill',inplace = True)\n",
    "train_data[[\"left_eye_inner_corner_x\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "centered-westminster",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,10))\n",
    "fig = sns.barplot(x = train_data.isnull().sum().values, y = train_data.isnull().sum().index)\n",
    "fig.tick_params(labelsize=12)\n",
    "plt.xlabel(\"Count\", fontsize=20)\n",
    "plt.ylabel(\"Location\", fontsize=20)\n",
    "plt.title(\"Missing Data of POI location - Train set\", fontsize=20)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "incomplete-compilation",
   "metadata": {},
   "source": [
    "#### Train Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "greater-franklin",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ImageId    0\n",
       "Image      0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_data.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "applied-liberty",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,10))\n",
    "fig = sns.barplot(x = test_data.isnull().sum().values, y = test_data.isnull().sum().index)\n",
    "fig.tick_params(labelsize=12)\n",
    "plt.xlabel(\"Count\", fontsize=20)\n",
    "plt.ylabel(\"Location\", fontsize=20)\n",
    "plt.title(\"Missing Data of POI location - Test set\", fontsize=20)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "empirical-affairs",
   "metadata": {},
   "source": [
    "### IdLookupTable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "finite-armstrong",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "RowId              0\n",
       "ImageId            0\n",
       "FeatureName        0\n",
       "Location       27124\n",
       "dtype: int64"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "IdLookupTable.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aerial-stress",
   "metadata": {},
   "source": [
    "## Visualize Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "greenhouse-trick",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "from mpl_toolkits.axes_grid1 import ImageGrid"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "intensive-melissa",
   "metadata": {},
   "source": [
    "Single image"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "median-investigation",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "train_dataT = train_data.T\n",
    "plt.imshow(np.array(train_dataT.loc[\"Image\"][0].split(), dtype=np.uint8).reshape(96,96), cmap='gray')\n",
    "plt.grid(b=True) #must be set every time the grid must be shown\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "polyphonic-carnival",
   "metadata": {},
   "outputs": [],
   "source": [
    "imageData = [[]]*len(train_dataT.loc[\"Image\"])\n",
    "\n",
    "for ix in range(len(train_dataT.loc[\"Image\"])):\n",
    "    imgIX = np.array(train_dataT.loc[\"Image\"][ix].split(),dtype=np.uint8).reshape((96,96))\n",
    "    imageData[ix] = imgIX"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "likely-industry",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 50 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(4., 4.)) #might be too small, adjust as needed\n",
    "\n",
    "rows = 5\n",
    "cols = 5\n",
    "nImgs = rows*cols\n",
    "\n",
    "grid = ImageGrid(fig, 111,  # similar to subplot(111)\n",
    "                 nrows_ncols=(rows, cols),  # creates 2x2 grid of axes\n",
    "                 axes_pad=0.01,  # pad between axes in inch.\n",
    "                 )\n",
    "for ax, im in zip(grid, imageData[0:nImgs]):\n",
    "    # Iterating over the grid returns the Axes.\n",
    "    ax.imshow(im, cmap='gray')\n",
    "    ax.axes.get_xaxis().set_visible(False)\n",
    "    ax.axes.get_yaxis().set_visible(False)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "precious-antenna",
   "metadata": {},
   "source": [
    "### Facial Keypoints"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "automated-effect",
   "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>left_eye_center_x</th>\n",
       "      <th>left_eye_center_y</th>\n",
       "      <th>right_eye_center_x</th>\n",
       "      <th>right_eye_center_y</th>\n",
       "      <th>left_eye_inner_corner_x</th>\n",
       "      <th>left_eye_inner_corner_y</th>\n",
       "      <th>left_eye_outer_corner_x</th>\n",
       "      <th>left_eye_outer_corner_y</th>\n",
       "      <th>right_eye_inner_corner_x</th>\n",
       "      <th>right_eye_inner_corner_y</th>\n",
       "      <th>...</th>\n",
       "      <th>nose_tip_x</th>\n",
       "      <th>nose_tip_y</th>\n",
       "      <th>mouth_left_corner_x</th>\n",
       "      <th>mouth_left_corner_y</th>\n",
       "      <th>mouth_right_corner_x</th>\n",
       "      <th>mouth_right_corner_y</th>\n",
       "      <th>mouth_center_top_lip_x</th>\n",
       "      <th>mouth_center_top_lip_y</th>\n",
       "      <th>mouth_center_bottom_lip_x</th>\n",
       "      <th>mouth_center_bottom_lip_y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>66.033564</td>\n",
       "      <td>39.002274</td>\n",
       "      <td>30.227008</td>\n",
       "      <td>36.421678</td>\n",
       "      <td>59.582075</td>\n",
       "      <td>39.647423</td>\n",
       "      <td>73.130346</td>\n",
       "      <td>39.969997</td>\n",
       "      <td>36.356571</td>\n",
       "      <td>37.389402</td>\n",
       "      <td>...</td>\n",
       "      <td>44.420571</td>\n",
       "      <td>57.066803</td>\n",
       "      <td>61.195308</td>\n",
       "      <td>79.970165</td>\n",
       "      <td>28.614496</td>\n",
       "      <td>77.388992</td>\n",
       "      <td>43.312602</td>\n",
       "      <td>72.935459</td>\n",
       "      <td>43.130707</td>\n",
       "      <td>84.485774</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>64.332936</td>\n",
       "      <td>34.970077</td>\n",
       "      <td>29.949277</td>\n",
       "      <td>33.448715</td>\n",
       "      <td>58.856170</td>\n",
       "      <td>35.274349</td>\n",
       "      <td>70.722723</td>\n",
       "      <td>36.187166</td>\n",
       "      <td>36.034723</td>\n",
       "      <td>34.361532</td>\n",
       "      <td>...</td>\n",
       "      <td>48.206298</td>\n",
       "      <td>55.660936</td>\n",
       "      <td>56.421447</td>\n",
       "      <td>76.352000</td>\n",
       "      <td>35.122383</td>\n",
       "      <td>76.047660</td>\n",
       "      <td>46.684596</td>\n",
       "      <td>70.266553</td>\n",
       "      <td>45.467915</td>\n",
       "      <td>85.480170</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>65.057053</td>\n",
       "      <td>34.909642</td>\n",
       "      <td>30.903789</td>\n",
       "      <td>34.909642</td>\n",
       "      <td>59.412000</td>\n",
       "      <td>36.320968</td>\n",
       "      <td>70.984421</td>\n",
       "      <td>36.320968</td>\n",
       "      <td>37.678105</td>\n",
       "      <td>36.320968</td>\n",
       "      <td>...</td>\n",
       "      <td>47.557263</td>\n",
       "      <td>53.538947</td>\n",
       "      <td>60.822947</td>\n",
       "      <td>73.014316</td>\n",
       "      <td>33.726316</td>\n",
       "      <td>72.732000</td>\n",
       "      <td>47.274947</td>\n",
       "      <td>70.191789</td>\n",
       "      <td>47.274947</td>\n",
       "      <td>78.659368</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>65.225739</td>\n",
       "      <td>37.261774</td>\n",
       "      <td>32.023096</td>\n",
       "      <td>37.261774</td>\n",
       "      <td>60.003339</td>\n",
       "      <td>39.127179</td>\n",
       "      <td>72.314713</td>\n",
       "      <td>38.380967</td>\n",
       "      <td>37.618643</td>\n",
       "      <td>38.754115</td>\n",
       "      <td>...</td>\n",
       "      <td>51.885078</td>\n",
       "      <td>54.166539</td>\n",
       "      <td>65.598887</td>\n",
       "      <td>72.703722</td>\n",
       "      <td>37.245496</td>\n",
       "      <td>74.195478</td>\n",
       "      <td>50.303165</td>\n",
       "      <td>70.091687</td>\n",
       "      <td>51.561183</td>\n",
       "      <td>78.268383</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>66.725301</td>\n",
       "      <td>39.621261</td>\n",
       "      <td>32.244810</td>\n",
       "      <td>38.042032</td>\n",
       "      <td>58.565890</td>\n",
       "      <td>39.621261</td>\n",
       "      <td>72.515926</td>\n",
       "      <td>39.884466</td>\n",
       "      <td>36.982380</td>\n",
       "      <td>39.094852</td>\n",
       "      <td>...</td>\n",
       "      <td>43.299534</td>\n",
       "      <td>64.889521</td>\n",
       "      <td>60.671411</td>\n",
       "      <td>77.523239</td>\n",
       "      <td>31.191755</td>\n",
       "      <td>76.997301</td>\n",
       "      <td>44.962748</td>\n",
       "      <td>73.707387</td>\n",
       "      <td>44.227141</td>\n",
       "      <td>86.871166</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7044</th>\n",
       "      <td>67.402546</td>\n",
       "      <td>31.842551</td>\n",
       "      <td>29.746749</td>\n",
       "      <td>38.632942</td>\n",
       "      <td>59.255347</td>\n",
       "      <td>36.065143</td>\n",
       "      <td>73.942694</td>\n",
       "      <td>34.624653</td>\n",
       "      <td>37.478531</td>\n",
       "      <td>39.398041</td>\n",
       "      <td>...</td>\n",
       "      <td>48.265961</td>\n",
       "      <td>67.029093</td>\n",
       "      <td>72.600433</td>\n",
       "      <td>71.862041</td>\n",
       "      <td>34.232759</td>\n",
       "      <td>77.339429</td>\n",
       "      <td>51.599453</td>\n",
       "      <td>75.963592</td>\n",
       "      <td>50.426637</td>\n",
       "      <td>79.683921</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7045</th>\n",
       "      <td>66.134400</td>\n",
       "      <td>38.365501</td>\n",
       "      <td>30.478626</td>\n",
       "      <td>39.950198</td>\n",
       "      <td>59.255347</td>\n",
       "      <td>36.065143</td>\n",
       "      <td>73.942694</td>\n",
       "      <td>34.624653</td>\n",
       "      <td>37.478531</td>\n",
       "      <td>39.398041</td>\n",
       "      <td>...</td>\n",
       "      <td>47.910346</td>\n",
       "      <td>66.626011</td>\n",
       "      <td>72.600433</td>\n",
       "      <td>71.862041</td>\n",
       "      <td>34.232759</td>\n",
       "      <td>77.339429</td>\n",
       "      <td>51.599453</td>\n",
       "      <td>75.963592</td>\n",
       "      <td>50.287397</td>\n",
       "      <td>77.983023</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7046</th>\n",
       "      <td>66.690732</td>\n",
       "      <td>36.845221</td>\n",
       "      <td>31.666420</td>\n",
       "      <td>39.685042</td>\n",
       "      <td>59.255347</td>\n",
       "      <td>36.065143</td>\n",
       "      <td>73.942694</td>\n",
       "      <td>34.624653</td>\n",
       "      <td>37.478531</td>\n",
       "      <td>39.398041</td>\n",
       "      <td>...</td>\n",
       "      <td>49.462572</td>\n",
       "      <td>67.515161</td>\n",
       "      <td>72.600433</td>\n",
       "      <td>71.862041</td>\n",
       "      <td>34.232759</td>\n",
       "      <td>77.339429</td>\n",
       "      <td>51.599453</td>\n",
       "      <td>75.963592</td>\n",
       "      <td>49.462572</td>\n",
       "      <td>78.117120</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7047</th>\n",
       "      <td>70.965082</td>\n",
       "      <td>39.853666</td>\n",
       "      <td>30.543285</td>\n",
       "      <td>40.772339</td>\n",
       "      <td>59.255347</td>\n",
       "      <td>36.065143</td>\n",
       "      <td>73.942694</td>\n",
       "      <td>34.624653</td>\n",
       "      <td>37.478531</td>\n",
       "      <td>39.398041</td>\n",
       "      <td>...</td>\n",
       "      <td>50.754202</td>\n",
       "      <td>66.724988</td>\n",
       "      <td>72.600433</td>\n",
       "      <td>71.862041</td>\n",
       "      <td>34.232759</td>\n",
       "      <td>77.339429</td>\n",
       "      <td>51.599453</td>\n",
       "      <td>75.963592</td>\n",
       "      <td>50.065186</td>\n",
       "      <td>79.586447</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7048</th>\n",
       "      <td>66.938311</td>\n",
       "      <td>43.424510</td>\n",
       "      <td>31.096059</td>\n",
       "      <td>39.528604</td>\n",
       "      <td>59.255347</td>\n",
       "      <td>36.065143</td>\n",
       "      <td>73.942694</td>\n",
       "      <td>34.624653</td>\n",
       "      <td>37.478531</td>\n",
       "      <td>39.398041</td>\n",
       "      <td>...</td>\n",
       "      <td>47.069250</td>\n",
       "      <td>73.033339</td>\n",
       "      <td>72.600433</td>\n",
       "      <td>71.862041</td>\n",
       "      <td>34.232759</td>\n",
       "      <td>77.339429</td>\n",
       "      <td>51.599453</td>\n",
       "      <td>75.963592</td>\n",
       "      <td>45.900480</td>\n",
       "      <td>82.773096</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7049 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      left_eye_center_x  left_eye_center_y  right_eye_center_x  \\\n",
       "0             66.033564          39.002274           30.227008   \n",
       "1             64.332936          34.970077           29.949277   \n",
       "2             65.057053          34.909642           30.903789   \n",
       "3             65.225739          37.261774           32.023096   \n",
       "4             66.725301          39.621261           32.244810   \n",
       "...                 ...                ...                 ...   \n",
       "7044          67.402546          31.842551           29.746749   \n",
       "7045          66.134400          38.365501           30.478626   \n",
       "7046          66.690732          36.845221           31.666420   \n",
       "7047          70.965082          39.853666           30.543285   \n",
       "7048          66.938311          43.424510           31.096059   \n",
       "\n",
       "      right_eye_center_y  left_eye_inner_corner_x  left_eye_inner_corner_y  \\\n",
       "0              36.421678                59.582075                39.647423   \n",
       "1              33.448715                58.856170                35.274349   \n",
       "2              34.909642                59.412000                36.320968   \n",
       "3              37.261774                60.003339                39.127179   \n",
       "4              38.042032                58.565890                39.621261   \n",
       "...                  ...                      ...                      ...   \n",
       "7044           38.632942                59.255347                36.065143   \n",
       "7045           39.950198                59.255347                36.065143   \n",
       "7046           39.685042                59.255347                36.065143   \n",
       "7047           40.772339                59.255347                36.065143   \n",
       "7048           39.528604                59.255347                36.065143   \n",
       "\n",
       "      left_eye_outer_corner_x  left_eye_outer_corner_y  \\\n",
       "0                   73.130346                39.969997   \n",
       "1                   70.722723                36.187166   \n",
       "2                   70.984421                36.320968   \n",
       "3                   72.314713                38.380967   \n",
       "4                   72.515926                39.884466   \n",
       "...                       ...                      ...   \n",
       "7044                73.942694                34.624653   \n",
       "7045                73.942694                34.624653   \n",
       "7046                73.942694                34.624653   \n",
       "7047                73.942694                34.624653   \n",
       "7048                73.942694                34.624653   \n",
       "\n",
       "      right_eye_inner_corner_x  right_eye_inner_corner_y  ...  nose_tip_x  \\\n",
       "0                    36.356571                 37.389402  ...   44.420571   \n",
       "1                    36.034723                 34.361532  ...   48.206298   \n",
       "2                    37.678105                 36.320968  ...   47.557263   \n",
       "3                    37.618643                 38.754115  ...   51.885078   \n",
       "4                    36.982380                 39.094852  ...   43.299534   \n",
       "...                        ...                       ...  ...         ...   \n",
       "7044                 37.478531                 39.398041  ...   48.265961   \n",
       "7045                 37.478531                 39.398041  ...   47.910346   \n",
       "7046                 37.478531                 39.398041  ...   49.462572   \n",
       "7047                 37.478531                 39.398041  ...   50.754202   \n",
       "7048                 37.478531                 39.398041  ...   47.069250   \n",
       "\n",
       "      nose_tip_y  mouth_left_corner_x  mouth_left_corner_y  \\\n",
       "0      57.066803            61.195308            79.970165   \n",
       "1      55.660936            56.421447            76.352000   \n",
       "2      53.538947            60.822947            73.014316   \n",
       "3      54.166539            65.598887            72.703722   \n",
       "4      64.889521            60.671411            77.523239   \n",
       "...          ...                  ...                  ...   \n",
       "7044   67.029093            72.600433            71.862041   \n",
       "7045   66.626011            72.600433            71.862041   \n",
       "7046   67.515161            72.600433            71.862041   \n",
       "7047   66.724988            72.600433            71.862041   \n",
       "7048   73.033339            72.600433            71.862041   \n",
       "\n",
       "      mouth_right_corner_x  mouth_right_corner_y  mouth_center_top_lip_x  \\\n",
       "0                28.614496             77.388992               43.312602   \n",
       "1                35.122383             76.047660               46.684596   \n",
       "2                33.726316             72.732000               47.274947   \n",
       "3                37.245496             74.195478               50.303165   \n",
       "4                31.191755             76.997301               44.962748   \n",
       "...                    ...                   ...                     ...   \n",
       "7044             34.232759             77.339429               51.599453   \n",
       "7045             34.232759             77.339429               51.599453   \n",
       "7046             34.232759             77.339429               51.599453   \n",
       "7047             34.232759             77.339429               51.599453   \n",
       "7048             34.232759             77.339429               51.599453   \n",
       "\n",
       "      mouth_center_top_lip_y  mouth_center_bottom_lip_x  \\\n",
       "0                  72.935459                  43.130707   \n",
       "1                  70.266553                  45.467915   \n",
       "2                  70.191789                  47.274947   \n",
       "3                  70.091687                  51.561183   \n",
       "4                  73.707387                  44.227141   \n",
       "...                      ...                        ...   \n",
       "7044               75.963592                  50.426637   \n",
       "7045               75.963592                  50.287397   \n",
       "7046               75.963592                  49.462572   \n",
       "7047               75.963592                  50.065186   \n",
       "7048               75.963592                  45.900480   \n",
       "\n",
       "      mouth_center_bottom_lip_y  \n",
       "0                     84.485774  \n",
       "1                     85.480170  \n",
       "2                     78.659368  \n",
       "3                     78.268383  \n",
       "4                     86.871166  \n",
       "...                         ...  \n",
       "7044                  79.683921  \n",
       "7045                  77.983023  \n",
       "7046                  78.117120  \n",
       "7047                  79.586447  \n",
       "7048                  82.773096  \n",
       "\n",
       "[7049 rows x 30 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "keypoints_data = train_data.drop(columns=['Image'], axis=1)\n",
    "keypoints_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "subjective-setup",
   "metadata": {},
   "outputs": [],
   "source": [
    "facial_pnts = []\n",
    "\n",
    "for i in range(len(keypoints_data)):\n",
    "    facial_pnts.append(keypoints_data.iloc[i])\n",
    "\n",
    "\n",
    "facial_pnts_float = np.array(facial_pnts, dtype='float')\n",
    "#facial_pnts_float"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "departmental-baltimore",
   "metadata": {},
   "source": [
    "#### Prepare data train"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "raised-potter",
   "metadata": {},
   "outputs": [],
   "source": [
    "training_data = train_data.drop(columns=['Image'], axis=1)\n",
    "\n",
    "\n",
    "y_train = []\n",
    "for i in range(len(train_data)):\n",
    "    y = training_data.iloc[i,:]\n",
    "    y_train.append(y)\n",
    "\n",
    "y_train = np.array(y_train, dtype = 'float')\n",
    "#y_train"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "capital-macintosh",
   "metadata": {},
   "source": [
    "#### Show an image with facial points"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "commercial-palestine",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "photo_to_visualize = np.array(train_dataT.loc[\"Image\"][0].split(), dtype=np.uint8).reshape(96,96)\n",
    "pnts_to_visualize = keypoints_data.iloc[0].values\n",
    "\n",
    "plt.imshow(photo_to_visualize, cmap='gray')\n",
    "plt.scatter(pnts_to_visualize[0::2], pnts_to_visualize[1::2], c='Pink', marker='*')\n",
    "plt.title(\"Image with Keypoints\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "inclusive-happiness",
   "metadata": {},
   "source": [
    "## Prepare and Split Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "moderate-travel",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(7049, 31)"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_data.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "noble-morning",
   "metadata": {},
   "source": [
    "### Build Model: Keras CNN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "genetic-anthony",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "agreed-cameroon",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
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