add Excel annotations, the converter to CSV, and CSV equivalent

data/dumitru_anotations.csv

@@ -0,0 +1,117 @@
+,image_name,hair (Dumitru),pen_marks(Dumitru)
+0,PAT_21_31_965.png,3,0
+1,PAT_31_42_680.png,2,0
+2,PAT_36_50_14.png,1,0
+3,PAT_53_82_940.png,0,1
+4,PAT_59_46_537.png,0,1
+5,PAT_61_299_74.png,1,0
+6,PAT_72_110_647.png,0,1
+7,PAT_75_114_73.png,1,1
+8,PAT_86_131_107.png,0,0
+9,PAT_104_1755_320.png,0,0
+10,PAT_108_162_660.png,0,0
+11,PAT_112_168_360.png,0,0
+12,PAT_115_175_283.png,0,0
+13,PAT_138_205_296.png,1,0
+14,PAT_147_219_544.png,1,0
+15,PAT_152_230_707.png,0,0
+16,PAT_170_264_785.png,0,0
+17,PAT_180_279_377.png,0,1
+18,PAT_220_338_339.png,0,0
+19,PAT_228_348_2.png,0,1
+20,PAT_229_349_256.png,0,0
+21,PAT_237_362_52.png,0,0
+22,PAT_243_372_640.png,0,0
+23,PAT_245_376_197.png,3,0
+24,PAT_247_1293_449.png,1,1
+25,PAT_262_402_265.png,0,0
+26,PAT_300_1478_445.png,0,0
+27,PAT_303_652_342.png,1,0
+28,PAT_304_653_446.png,1,1
+29,PAT_323_687_169.png,1,1
+30,PAT_343_717_927.png,3,1
+31,PAT_344_718_206.png,0,0
+32,PAT_360_742_782.png,3,0
+33,PAT_365_751_709.png,0,0
+34,PAT_370_758_322.png,3,0
+35,PAT_375_763_732.png,0,1
+36,PAT_417_828_723.png,1,0
+37,PAT_422_837_683.png,0,0
+38,PAT_432_851_386.png,0,0
+39,PAT_435_854_68.png,1,0
+40,PAT_443_864_894.png,0,0
+41,PAT_453_883_719.png,1,0
+42,PAT_513_964_343.png,0,0
+43,PAT_531_1004_189.png,1,0
+44,PAT_547_1033_911.png,0,1
+45,PAT_566_178_625.png,1,0
+46,PAT_570_1084_637.png,0,0
+47,PAT_579_1099_551.png,3,0
+48,PAT_587_1117_880.png,1,0
+49,PAT_596_1146_294.png,2,0
+50,PAT_619_1175_767.png,2,0
+51,PAT_636_1204_521.png,0,0
+52,PAT_637_1217_274.png,1,0
+53,PAT_637_1434_684.png,0,0
+54,PAT_645_1223_443.png,0,1
+55,PAT_646_1225_590.png,0,0
+56,PAT_660_1249_373.png,0,0
+57,PAT_680_1289_182.png,1,0
+58,PAT_682_1292_986.png,0,0
+59,PAT_690_1309_981.png,0,0
+60,PAT_705_1326_82.png,0,1
+61,PAT_745_1406_409.png,2,0
+62,PAT_789_1483_793.png,0,0
+63,PAT_795_1508_925.png,0,0
+64,PAT_796_1509_400.png,1,0
+65,PAT_814_1532_545.png,1,0
+66,PAT_815_1533_460.png,0,0
+67,PAT_819_1541_727.png,1,0
+68,PAT_830_1564_54.png,0,0
+69,PAT_834_1574_397.png,0,1
+70,PAT_851_1623_815.png,1,1
+71,PAT_867_1650_825.png,0,0
+72,PAT_868_1657_698.png,2,0
+73,PAT_886_4635_304.png,0,0
+74,PAT_904_1736_851.png,0,1
+75,PAT_920_1747_19.png,0,0
+76,PAT_931_1763_617.png,0,1
+77,PAT_978_1844_715.png,0,0
+78,PAT_987_1859_724.png,0,0
+79,PAT_988_1858_944.png,0,0
+80,PAT_1036_169_687.png,0,0
+81,PAT_1062_264_741.png,0,0
+82,PAT_1064_272_668.png,1,0
+83,PAT_1064_273_980.png,0,0
+84,PAT_1067_284_533.png,0,1
+85,PAT_1074_322_174.png,3,0
+86,PAT_1089_375_60.png,0,0
+87,PAT_1092_378_922.png,0,1
+88,PAT_1216_759_542.png,0,0
+89,PAT_1216_760_593.png,3,0
+90,PAT_1221_766_430.png,1,0
+91,PAT_1245_845_32.png,0,1
+92,PAT_1274_954_677.png,1,0
+93,PAT_1326_1156_139.png,0,0
+94,PAT_1347_1226_928.png,0,0
+95,PAT_1364_1246_583.png,0,0
+96,PAT_1404_1393_369.png,0,0
+97,PAT_1408_1406_950.png,0,0
+98,PAT_1414_1429_53.png,0,0
+99,PAT_1414_1433_806.png,0,1
+100,PAT_1428_1489_454.png,2,0
+101,PAT_1432_1497_328.png,0,0
+102,PAT_1545_1867_547.png,0,1
+103,PAT_1554_2393_541.png,0,0
+104,PAT_1582_2574_905.png,3,0
+105,PAT_1591_2648_855.png,0,0
+106,PAT_1798_3455_379.png,3,0
+107,PAT_1822_3576_145.png,1,0
+108,PAT_1875_3689_646.png,0,0
+109,PAT_1884_3730_813.png,0,0
+110,PAT_1946_3924_24.png,1,0
+111,PAT_2018_4167_11.png,0,0
+112,PAT_2024_4221_632.png,0,0
+113,PAT_2061_4395_587.png,0,0
+114,PAT_2068_4424_995.png,0,0
+115,PAT_2162_4820_913.png,0,0

data/excel_to_csv.ipynb

@@ -0,0 +1,154 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "e5d1b51b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "b1be684d",
+   "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>hair (Dumitru)</th>\n",
+       "      <th>pen_marks(Dumitru)</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>count</th>\n",
+       "      <td>116.000000</td>\n",
+       "      <td>116.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>mean</th>\n",
+       "      <td>0.586207</td>\n",
+       "      <td>0.198276</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>std</th>\n",
+       "      <td>0.933148</td>\n",
+       "      <td>0.400431</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>min</th>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25%</th>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50%</th>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>75%</th>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>max</th>\n",
+       "      <td>3.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       hair (Dumitru)  pen_marks(Dumitru)\n",
+       "count      116.000000          116.000000\n",
+       "mean         0.586207            0.198276\n",
+       "std          0.933148            0.400431\n",
+       "min          0.000000            0.000000\n",
+       "25%          0.000000            0.000000\n",
+       "50%          0.000000            0.000000\n",
+       "75%          1.000000            0.000000\n",
+       "max          3.000000            1.000000"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df = pd.read_excel('dumitru_anotations.xlsx')\n",
+    "\n",
+    "#### Removing the unnecessary commas at the end of the photo names\n",
+    "df.image_name = df.image_name.str.replace(',', '')\n",
+    "df.describe()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0e891ff7",
+   "metadata": {},
+   "source": [
+    "## Saving the data as a csv"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "7a2a6470",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df.to_csv('dumitru_anotations.csv')"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "base",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.13.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}