Commit cd669543 authored by Quentin Chabanne's avatar Quentin Chabanne

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parent b8b71e66
{
"cells": [
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"# Calcul de l'objectif nécessaire\n",
"\n",
"Le but est ici de calculer les spécifications de l'objectif à utiliser pour l'appareil photo.\n",
"\n",
"Rappel des contraintes :\n",
"- distance horizontale entre l'appareil et les arbres : 300 m.\n",
"- résolution de l'appareil photo : 16,05 Mégapixels effectifs\n",
"\n",
"Il y a différentes résolutions sur l'appareil photo :\n",
"- 3456*4608\n",
"- 3264*2448\n",
"- 2336*1752\n",
"\n",
"Un rameau doit faire environ la taille d'un pixel."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import scipy.signal as sig\n",
"from matplotlib import pyplot as plt #library to plot figures"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"d = 300 #distance (mètres)\n",
"taille_rameau = 0.055 #taille approximative d'une feuille (mètres)\n",
"\n",
"# résolutions (pixels)\n",
"resL = [4608, 3456] #résolution maximale\n",
"resM = [3264, 2448] #résolution moyenne\n",
"resS = [2336, 1752] #résolution minimale\n",
"\n",
"larg_res = [resL[1], resM[1], resS[1]]\n",
"long_res = [resL[0], resM[0], resS[0]]\n",
"\n",
"res = [resL[0]*resL[1], resM[0]*resM[1], resS[0]*resS[1]]"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"Pour trouver l'angle d'ouverture qui nous permettra d'obtenir l'objectif nécessaire, il faut utiliser la formule suivante (à partir du théorème de Pythagore) :\n",
"\n",
"$\\alpha = arctan(\\frac{T_{rameau}*T_{image}}{d})$"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Angle alpha : 0.56 radians\n",
"Angle alpha : 32.4 degrés\n",
"Angle alpha : 0.42 radians\n",
"Angle alpha : 24.2 degrés\n",
"Angle alpha : 0.31 radians\n",
"Angle alpha : 17.8 degrés\n"
]
}
],
"source": [
"alpha = [0,0,0]\n",
"\n",
"for i in range(3):\n",
" alpha[i] = np.arctan((taille_rameau*larg_res[i])/d)\n",
" print(f\"Angle alpha : {alpha[i]:0.2} radians\")\n",
" print(f\"Angle alpha : {(alpha[i]*180)/np.pi:0.3} degrés\")"
]
},
{
"attachments": {
"angle-de-champ-par-focale-en-24x36-1.png.png": {
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bZmtQiAragH3X+bqLPVzb1k9gd/3ZBFn7LeSk4GUjRGyiWG37Cps2DZs2bRo2bRo2bdo0bNo0bNo0bNq0adi0adi0adOwadOwadOmYdOmYdOmYdOmTcOmTcO2v+YJIbAvtNAMaNg2bUHoW4HBbcsnmgIN22YtijgXnm9z28d+uMJzhXJzwpVLunOuhm1tZps4ZlWXwB8+jWD6dmhGli3UkmnZXMOhYVtTyGZbYeQyAI138XnVqEuCjsm71DCbhDUjHpoaDg3buuoHQBqdgc2WCz4OrGWIETNsW8OhYVujktp8KqPLsEUaDg3beowzzrqBgRUE25uDLQLY4Bvt2c4QbDuu7RHf96mH/6iagBkZ3CJGZBqmbQiLQW1Vw3E2YPMC24rkyMEWq1YCpyaOehaYplktLesJNbxFvLXrwice/uOKyVL2AcCezcAg8Mo0RnsNmxmwEFyH63eC2M25ytmdLmVbENFRZIgwqgrbyjpsmnRkG3SkYTuAmI1amN0KJWyBHVmUYm4Ll8zAz81yAY6mBcoX+x9CWRRwkwpwebhEzS2kyUTIDHOSIQkC2CeLmFoicknbvsAG1T0SEkvCRpsBa9okNI0Al3xi5UZMhMKmpBnJeQwM2NrsWiZsRpq+OQpNy958UGhanmFbsWOzm6bdhYOAuE8tNTVtewNb0CWub4pQjjcLXs4DHwcVwSA0DIui18q70/6I4QwWoS9Hv2sSrD8GI5fAEpTDuht3bWIU4HQdUTNQeRQDdx1S3DsH0iydFd4X2IIuA8fm+6OQKdhcvE2AS+hK2AoMpkVHciBx6UGQLdiajQS2QOHS5mGjodLwyJ84atg1IHaaRdG2F7AFXeoKVwg+9Wyu8gkT2PI8G9ZEuzhwMfo0BZv0bNuDTcABy5qMysgtw6Y9237AxsPQ9m1wTJ5KfVDfcCEEMwEXCPl9ih9k1w8i2xxhTswMTU/KqIKtKyYy2iwF29fvf1zasaFj5bZph7KPkh8pGTXxOFBGtWfbE9hcjiZnOJDxveCGB0vwj+DyM5GHCglwqjIexHOK8kAYDGM4T8ASYfKDwvbx+3957lbZc2D4M3EZDfjkLe6aEbXEcUnbvtRG98X+eesPz4Hd0ixo2DZsXyvUtgsbNzGEIDY2mHnUj4iG7ZDsyeeVNkP9fG77sJkWdm0KTewKQEfMtoSG7XDs7uUbFfTz4z88d2rbhE1gtyasd0c2VsJVj7oginwa+BFEe7aJS2evr/BZgO3zd69dKw3bVD93AJvsQxfZAJiF6RJXttnRJg2aPsNWlI5csiIN276Z+/DytctlYfv6VD/3BjbLMCa5Rg/zdfmtKBq27Zp3A1C7XA427+P3n1uyrcOGqUTTx07BYjTTimLGsFEN294Fa+8iaqVg+68F/dwVbKTJhEwBu3TEjaVWFO3Z9i1Ye3hZsVYctmX9XBNsT5+WgQ3xMkNsRCFW3M0KYUN/ptqH/WLtwxq2baU7bkxQKwxbkn6uA7Yvr189vl4mzpQTFKlpigRRtc64FYUXb0XRsG1dQQvDlqKfK8N25/X7x7dv375uaDsI2J7crZDuuHy5DGyp+rkSbE/fef3+pdu3L126pGE7ENievFsyc+E+vDzHWi5sGfpZHbYHIJ6KNA3bwcDmvlsuTebdWEAtB7Zs/awGm6fE89LUNGwHAVvZBoC77y6ilglbnn5WgO3LqXhq2A4Lts/LNQB8/vDaMmvpBeTrZ1nYUDxvL5CmYTsM2O6iJBaG7cmygmbAVkg/y8DmvbMgnhq2Q4LtRqmcbJKCphbw9a2/PPfcGmH78vrVJfHUsB0QbDfKtDalopZUwMfvl0EtF7Y7yeK5LtggCrx6R8O2DdYKwfb5w8uprC0WUEY/82F7mi6ea4DNu3MdigeX+Y6GbYPmPbxWOCfr3Uh3a4sFfF0etXTYssVzRdgegEO7H3tMDdsm7cnD4k2bdzNRmyugrH5mwRa3RF0qYGVhe/oOUIwObVK6hm2D5s7wkwNbcrojCbZ/VnFqybA9TUimrQc270EsnHOFa9g2mF4r3I6elu5Yhu3ryqgtwvagoHiWhu3LGeFcKEDDthXWMmG78W4uaqqAivq5BNtSS9SaYHt6Z0E4NWxbTOUWge1uEdTAbnz8h+dWsltTz1PSpRWCDYRTusqs3ImGbVOsFWttykx3zG7/4RfPPbc6bA/ykmlVYEsXzuqwcYJPmnqq2yUnroYtQxmLtTZ5N4qhdvLh0dHqsFUSz2zYnt5JqgmsDhu1rJAZwrZwIKUgtHyuYctL5ebAVlBBT+4dHa0M2yd/fHRpBdISYJMptEsl/GQJ2BgRkeWZlmBNwruBKwdM8oggxBDY1ZyrJVfDdprKzYQtP92h9FOithpsn/zj56+++ujSajYD21Q4S9FbLmYLQmFRfOIUn47BP8P1LT+M7NB2jcmSOO+wPXlYpIfQk0IKeu3Do4l9Udml/eNVaeuBzSsjnKvAZkcCB23wKT5+Kkc+dC3bpU2GI3H6vht0mBrV4TzD9iRRGxdhK6SgJ/eOjlaD7ZM//vzVia0G2/HxpetFawLrgM0ccflos6Vgw3EJ8TlA1hXuKMBBL/HJVIzozjNsn79boDtaEdSm+lkVNnBpp6StBBuAdun2zY8ulRbO6rDRETE8y8Rn6RE0HLZ8ATZ0dup51HMLWwprc7C5BdIdM/pZCbapeK4I2zGAdvvmzY+eBbu5qg4Xhs2jTUqYG3RZFAoRRqyLLgwfp2dN4XYDfJweh3kdnWvPdvdybt9Hr0CDwcm9o6MVYJsVz+qwSc7AoUnQJGzH24JN2Gjco7ZNcExBm2K904sCWBauzQy1ZETnOWa7m99pI19BF/WzHGwJLq0CbMqhnXK2Zdh0C0KFVO4SbAV6d3x4lGxfVHZp5WCbFc5nNWz7CtuNazmw5ac7Tu4dHVWF7ZN/ZJBWDLZF4dSw7StsD/M62uYFayn6WQS2dPEsCluicGrY9hO2J5msAWyf56J2lGlfVBPPArClC+cBwyYmbfjqjThLsD3JQ+latoKe3Ds6qgRbnnjmwBan0HJBOzTYmOWH1PBMy4pcg1iWxc4ObHlu6+TCSWX9TIetiHimw1bUoR0kbJwbtIuJX94NPADOlPO2cg6ezkU3h0uet3aH98zuWTt5fCEDtjz9TIGtoHgmwlaas53D9vTBneuvv/6gjI5GthxC2o54l8gp3gwjCu3Qti2LG+ZILoXk4GC7mymR1wC1dNhO7h0dlYZtsSWqDGxlhHP3sD198A5AdvW+avsv8ZSzGTaJnDfQtLFhS7XZR6FgTeqGJja9kqbprnvK1Ge2wFoWaicXLqTD9mFR1GZgKyees7BVc2g7gW0eskmLbAnYBIl8YQNL0Sxsau5KO8LhfLGdX01ueUCw3chT0DTYCurnHGylxXMGttvVHNpWYZtAdjwH2cRKjd/AmwRHiPZN7KqkZmddgC04ONgyU7kT1BJgO7l3dFQOtqouTdqbn/3+2RVtk7BJyK6mQVYetiAgtuWSbhBAsGbjZDI4lHQ837gf4ZLoHhxsGem1iYImwVYWtaOj6i7tzTc/+zHYXsJWDLIKsNk2TgXIbJvJuoIp653UNIRNDJMaAS4xg9IDgs3LYG0WtXnYyukn2JWLFy9W5UyCtnewfVkKskoyetZaEDKaDU4eX0iB7eTD8qRdrEDbDGf7ABtgdWcC2f2SkGnYstJr1xZQO4WtpH5OSCsHWyycP94H2I6PVcc4qAbfv1oRMg1bOmvXTi5cSITt2of3qoFWHLY3Fx3armCTjCnIPoorwTdXe5bwPMOWmso9eXwhAbZ3y4VqC6QVgi2Vs23CNoHs5ilkE7u9YtC3XdhcbMp3J+353k5hS2PtWhJqAFsZ/VwmLQ+2ROHcJmzHGZAdJGyBZQXYhB8GhmeGVrFHVDcE243iCnrhwuML9+6tBFoWbG9mO7QNw1YEskOELRgxz/Dk9JX4WL6Qz9a4BHsuYbclL17ytgFbSio3EbULF+5duXJlNdJSYCvI2QZgm4esWAG7gs2DOrBsmLj6ZeHWrtBkzMPmBt6VDRFyukoe+n4Ywf+GsCy15G0etuSUR1Kw9lihVgS2i9lW0aGtGbYqkO0Ctqdf3nnnOqbyfgf2zMQKF8CafhSa2FdEjFgU4VA3OMRI1/SiJmdN7oaRazY5aZJNw5acyr2WiJoiLRe2KxdzraJDWy9slSDbEmze0wd3lAOb5WvOCsOGrVysG4wWYWM4RS84O3xSOggNsTAAxPphSx7M4yRNP/NhK0DaFLYCNYHNwPbiix+t1Iy/GdiSHViqFfdsOO14l0HtgHQ58KVaUWPYyAQ2j28atsT02rKCPp5DLRW2YqCB/by8cK4FthfB/o+0F1d1jbdXbII4frDkwAoAVgk217eZ7UM1lNnYU4QGkipsxaehAeKJj+UHXQ8/2CRsSaxde5yhnxmwFSbt4sVP3/zxivb7qpBNbPuwHccWJ4dvVuGrGmwGj+yIG8LEV2zPl6OKYCt+EBnc5vhYPos8/GCDsCWk15IUdBG1BNgKk/bppz8Fe2VLsC1Dtl3YFvi6+dG333777PPKnlnVNp07eWbTrJ3k6GcSbFcKcyZB2wJsL6ZDtnHYjjMAe/v5GTtfsN3IDdYeJ5I2B9uVMg7tp5uGLR+yjcA2y9ftCV9JgJ1b2JZSucvBWgpqU9iuVOBsE7AVZ2ydsCm+khQyFbDzCtsiawvB2uMM1K4UBe3TJNDWCFsFyNYF24sLDqwYYOcTtqVU7ryCPs4gTVo1h7ZG2KpCtgpsMhR8+z/A3nrrrdJwnVvYFlO5iwqaidoPP/ywAmcrwvaGsr/9x3ZgU3xNAJu1g4RNPSUhMy7ffPPNna3AtpBem1PQx9mo/SBtFdCqwfbGvG0StjkHlmr7DtvTL++oxohnnnn+m29+8Ytf/vKXf/rTr8D+bWrvbAO2BdZOiurnD1NbgbNysL2RYuuGLdWB7TFscx1BpMN6Bh3WL37xPXK1AFaC/WobsM2n1+aDtXsFSEuA7dMSoBWD7Y1sWwNspwr5VhXbIWzgqZCpb1IcVlHbBmx304O1e4VIW4CtJGfZsL1R0KrC9t/Sfvazn721qm0Htuefl0jFUFXFamew3UgO1tL184cEW4GzZNjeKGklYJvyNWf7B9u3scNCriYyuDawdgPbbHrtVEFTUfsh2coL57x9VhWygrAlA7YvsL399ttv/fk3m3JY+wPbDGtTBU2tf/6QZqtwJu1fb6xoCbDl8rUL2JArAOs3v/ntb3/7/ffff/fdd+i3/h3t33ZtG4ZtJpU7VVBArQxoL6BVh+0DZWuC7b/LAbZW2JK4elty9RvJ1fczXCXaGYdtJpV7klkpyAKtGmwfzNtqsL300ht/+9mKVoWvmYrrn/8877CyuTqHsLnT9NppsHavIGgvzNmnlSmrCttLC7Zx2ObAQvsJGKD1I7Dvv3/55Zf/fVU7WNg4L5HKjYO1pFAtn7OisH2Qaf+qAtimYEvk6iczXCn77tRePtewBaQwa3Gw9rgQaS8k26cVGcuF7aWitgbYZrlSYKVxlWjnEzbid+q9Vr/usyLNBhMFvZcH2gsZ9mlVyJJge6mKVYDtJ6eGaC2D9XIpO5ewBUNn0OjVar12i+Q2G0gFXdLPMpwtwPZBNfvXSyva30qBlWAvl2RLw4bWHwzHtf643amP63ZnFDHOWBAwwsA4vrjT9JpU0MfZpL1QxD6tAtgrp7ZO2PK5SobtZQ1badjYcNgYt5rjcb1TqzWcwWDYABvD/+Nxb9yG11qdKNZOlvSzAmfS3ivP15ytCNtrr730f3+0omnYKsBmOsNGe9hv//Wv7V6t1RgOh4NxD2FrgY3HrVZ/6PzPw2mwdi+FtBdK2XsVAKsG22sppmHbCWzgytrgz9qNYa3WqrXb7Uar32i3ewgbxHGtfttpPlTBWjJpL5S398rzVQC210qYhm0XsFFnOKw1Bo4zaNeAtlatBoLa79T7UGeA5X6rPx42H57MVgpW4kzB9kp5wObsjddWNA3btmHjhAThYDBoDMG9QazWbo97wNjIalpWp9UHa9Xr9db4f05OUasO2t9P7acluPp1kr30lYbtsGCjUBMYSoPaQK8nXRk6t37Xsu0uqGi/jtZv/e+FedJKw7VoPy0DViJs2rMdHGyyxjketxsgmhij9aW1OqHvN/GdhK3e+t/CoP29mH3w6+JcadjOBGwM3Nm41+pjoKb8WktZvdPp1PFNX75tf3Uli7N8tt5btA9+/WsN2/mCjYNXazR8zOC22rO09Wv9fk0KK7q+9uCvVwoD9l4h07CdP9iApUa7X/f9qA+wxUEb+LkWBHNt/MMXqD38vx8SCXuvsmnYzh1sAmFrtFutJsAmqwiTOsIQQrnGxBC299ZrGrZzCtu41qrbCNsMbsO2cmro3NoNDZuGbV0y2u807ZaETdKGwA2Hsm0U6qmY2HWkjK5NQzVs57aCADFbvTOqzcPW6NXasrYw7kNVYbmCsFLtQMN2flMfmGYb1uZYw7+WhK2Habfhf16pnvnQsGnYZBv8EOqcbYzK2v24aiCtJ5sRZMUUm+Nrja/uTZO6a8np/l3Ddu5gC8a9gTNAUzUBxV27Pa716v2WbCqVnw2/OrlQvrWqbHOVhu2M9/rwok5/EPeXjHkbN4Y9jODass1UpT6+Opn2L6rYDl+wbbQwgRq2A+1ihB3apEcbKtaG7d5w2kSPnSkHX70713Fy1S5Gf3/hvVW6FwFruovRoXae7A3b2NxeGyJxQxTVMXallKKKr0PntYeyn+7MQAur9Z1c6Dz5yjo6T2rYDqOn7rD9n2A1qaMygmvDZ0OopvYamAAZOP/7bvwEQnIXyvLEvbdSp/Di3cI1bPsG22AwnsI2RFEdDAE2WVOQ6tqrcznGx2QomXvbeuBlHc8gpAGoYdsFbGI8gW04bjRsRghnhJr4KB9hnBDCxHT0IjXuwuOMB6yK9qtc5Tm+dT7KV/E5Pg1bRdigJiBh62FHD5YzLtvJ46RRPqo/pPzBPj6kXAhADVuV50YHgwlsYB2WM7rpREtzHlUuO/zCB1WHX9jQE/H5j8gvjunxnYatyEPKg2EPYRvLTmztfsSzx22eDDj5OH+4jx9eKDuwzAcrDSyz2bE+5m1pVJnvy4wqc95h68m2q3prOLZzRqSfGYz+3oaGzKo6ilFh8DYxPtvSeFk/SgLwu/M9/MKwh3m2caM3bLWHWBOleXNtnGSMRr/WwQBXGp8ti7ytjTy5DOD35xc2ju1SsqckvLSH7UGtN+jnzuxyOib948KDT/7wQvVhTj9Y3zCnW4ZtfjTKGQIXBmU+H6MYYU9J1Qd8DLgNe9Zo2PfSBtU9nUfo2uPsyaoygft0xfGb1zOA8wrDN69/AOf5UcGLjLJ7iLD1hrWaeryl0a41hjW7nw7b3MyPc/MI3SszMv0+Dk1fFrytDE2Pw4enusDDbK6qtRv4fMu40W7JZw6GVkYJM7TNTsaXMuvGDxmTbqwC2ysrzrmRPelGEZe3s0k3pgPY43xm0xk3fnUQsHVkD6N+/OReuwdK2hdFp3iZnbmq1NQb1aZHS59O6I3NTSeUAt6eTSf0/LbnEqoEm8vsems86VLUaPTqkVt88qqFOfkKTyq04jxpqROlvbHZidJmXN4BTJT27WSWtA25wIqjhXPLDMzItiPKRMlp+S6fFJxDOWcKyJ+udQrIjc3KdzoFZPkZRvdiCsgZF4h/q8x7VXVoepI/NH3qhKNz8yhnTqScPbltGeBeWXFu2zVPblsFvJ1Pbvu7+G4+uDOZ2fbbuZltNwbbitN2L8wQnz/F7YqzdpeftvuNrU3bXXTO272etvspAvj67Jzdf0ogcDuwLdK2GLo9zpsm/mKm5RNXfo74Beg2OUd8MZe373PEL6e9Tl0gEAgu8Ps724FtNr2bGLqlzNU3sYu5lg1cZdgm9vvtwLbs8qbgHRxspW1tsM3O0JcUumWr6RFYAeDSiVsdtsnt3x5sC+B9dPNbsGc1bIVskbZFLc1S06OjorwlJ+PWA9usz9kubGC3j8EuXbp9+/ZNsI/Kg3euYJtL75bE7WhqFy9erODi1gtbFejWANul2I6VXULyJuAVIO98wTaf3k3R0uRUyNGsXblYmrjNwFYGujXCNmuz4C27vLfPMWwL6d3kNEiieztasKK8TYDbLGxFoNsQbJnkzYN33mBbSO+maGkCbkcJdvFiceI+2wpsc/XIHcCWCd5Hv/udzEKcH9iWEm4p9dJFNT1KtsIO7uKbb3722dZgS3J124ZtmbwHmHx9oLKvV6uQd3CwJdKWpKXz7u0o1Qry9iraCsT9ftXMxbMf7RA2aYusPP3yzjtT8jYNmwf/yzZOb/p+ae739cO2nN4tgttRpl0pCJsirhJwv1/VMd08vhTL2b7ANsdCEZe3AmzU4oYZ2cwzLZyAm9iW6Rq+uXHYltO7iU0K82p6lGdXCsNWzcWtA7ZLx5NUWRXoNgrbksu7fn0ZvOqwkW6Xe5YIomBEzC4XoUlGVIRk87DN9RXPCd0m7u2ogF0pDlt54tYC21wIVRa67cE2D96py3tQ9Ya7vh1yg9o286khRoyNhEF9ZhpbgC0pvZuupcq9HRWzKyVgKyWqa4WtEnS7gW0tRn0ygviMCADNMCxKfcNA4LYDWxptSWkQtJPLJ0VxS+Ht1Qwr4uI2AlsydB+dNdhIl5EuwSqB6O4CtqT0boaWnuA3Hx4VtnKwTYjbGWyFoDtc2GjoW10fq56uRQ03DILQhSqDtzXYEtO7qbidqG8+vFectyslYcsR1a3AlimvNy8dKmyuEEx5NsO0eNDlvBtwyzS2B1tywi0ldDuZymwJ3OZ4e7WwJYvqVmFLhO74/vHxbWkHF7OBkoYqpyZsywoMI7B8W2wTtgzalkK3kxkSS6jpjKC+Ws6WRHUnsM1Cd+kd40vZ8/V+Veh2CZvLJ6LJJWSCb6UFYfYI0mlb0NKTue/KqGns4F6tYrMubqewod0+7cB/Ct2lMtDtErYdNVcVSO8ua+nJoucrh9vRlX/8/NVqNhHVfYKtInTnHLa09O6Slp4ss1hOTb947pM/VuVNErePsE2he1AIuvMOW3rCbV5LT5K+LaOmXzwH9skf/1GZt0e3q7dqbhq2gtCtAJsc80A9K+xNP+Dk0GDLpG2K20mK77tXCjYJXEVBfXQsb2F14rYA2zx0VxehqwwbsX1btjYFBrNtT7ajR8Kwo4ODLaGv+HLodpL69YclYZMOrgJvjybVwku3b978aL9hS4GuKmyuZXLbNizObCPyLdcQVkQs0w3Z4cGWnt497Q1ykkFjITWdha2SoD6aTUTArS/t4nYA27QxXUFXtR1ddAPD9GU7uuGx0DVYlxtBSEzvAGHLow209CTT+xVQ0wXYygvqo6XMV0kXt0PYVrWga49I3NdRtTQp4IxDhC0rvatwy/4acPuwPGzlBPVRcq61OHGHC5sb2dSajIs2adY8XNiy0rvSbtzNWSFPTZNhU4L686qwTUS1UL3hcGFDrkiTnMKGHTaCkThU2DLTu0DSDePJjct57i0Lt1TYijq4RznNSbku7oBhazI3mDgyhI2PqPAj42Bhy07vAmygtQ9XUNNM2IrUGB4VacDMqjccLmwetWw/mMRvEK8ZzMJcyOHClplwk7BBRSJPS9NTIXmwIW+ZNYZHRVvM00T1gCsIhuDuaXeh1Hb0Q4Itg7YYNsPL19IUNS0AW7agPiqORbKoHjJsZ6W5qlB6dwIb/LAeFsAtIRVSELZ0QX1Uko2lZJyGbb9gS+8rfmMmTfIwn7ZlNS0OW0oK7lEFPiaiqmHbR9jS0ruzsBUK3ZZSIeVgSxDUR1UhmYjq7ePqfWyrw+Z5ie3o8uETcs5hS0nvzsNWJA2yqKalYVsU1EcruaXj49vX71y/ev+4eq/uKrAJKvtg+5ZqR6fYpA4BPvMt6hmRfd5hSxkK5MbiWvlpkHk1rQLbnKCuBhuwch2P+8E7r1+9f6kScFVgY/aIGoYZEMs2fEJ8w7RDYZBuwLqBZ7FzD1tiencJtoJaeqqmVWGbCup6YJPN4neuv37/uDRxVWDzDEtNBUtDI8AeQh4m/03fALfGTVfDlpTeTYDN8G4Uw02p6QqwKUF9tFrENQObtC/RxZWK4qrFbDFsth23oyNs2A8t4anNcwlbwkjPSbAVTIPEaroabGC3rkv9Wxds8udSSlRXgS3oTioDGrbc9G4ybAXTILKAy39YFTbQv3deR2e0Ntgmonq1kKiuAFvQnYZnpzKqUx8p6d002IqHbneNj99fFTa0O69frZbCSIOtsKhWhy1oUiFiR8a6AhvWoY6gYUtJ76bDVjANIgv4+v2/rAwbklFJUDNhU6KaXW+oBpsfGNwK7Wm7ObMEaqi1f7WDHcI2n97NgA21NB+3uID/uvWH1WEzKglqLmx5oloNNuEaLhecTx5Id6WL20w7+uHCNpdwy4StiJZOC/CqqumtxZ0+uF5KUIvBZkyTcUtl6+aqLdGWA1t+b5DZAqqp6a2kUKuEoJaATZ7RUjJOw7al9G4ebLlpkPkCqqjprTQoCgpqSdjiesNMC5eGbUvp3XzYctIgiwX8s7Sa3sqQvSKCWgW2U1FFF6dh2056twhsmaFbQgEl1fRWdmAPNYZsQa0MW1xveP2+hm076d1isGWkQRILKKWmt/KjrExBXQm2c2K7hk2ldwvClt4bJKWAEmp6q8juH6TXGDRsBwCbTO8Whi1NS9MLKKqmtwruPy0Fp2E7BNgwvVsCtuTeIFkFfF1ITW+VOOKkNi0N20HAhgm3G2XWf7KcBsku4J8FcLtV7piXUnAatsOADWi7UXKDh9fKwAb2cZ6a3ip91POCqmE7ENiMz++W1t55LS3gGnPU9FalAz9NwWnYDgW2CjafBimkw0+ycLtV9UBiQdWwnWHY5tMgRYO+dDW9tcKRYArukobtLMM2q6XFaxhpanprxWN58KWG6UzDdtobpEx1Nrlh4ZZmQcOWY3FvkHK5k6Qu5DuBzYv707o4Qjfz1EL8sSCehm0vQ7eSsCU0LOwANo/6ViSfvwuZEdgR5ZGcZYz52Kvb9DVs+xm6lYZtSU13AZvJSBiBD7OazLAZ94lJaJPwLiVdaviBoWHbyzRIBdgW1HRHMZt67A48G8MH2kFHRyywPPhYmELDtqdaerfadqdquiPYfBNElOOwHPKBdhxMGR/5xJFtdQXhzNlETXcDGx1xYZk8DGI3JkLT0LCdZZNquhPYaJcZxPL9UTxzj/Btz6CWUlcN29m0r9/fTW20GQjuea4YBbLmyX2Lc0GaAR9RDdsZxu3r7e+Th5Ytp1J3fRY7Ot+3AiOwpvOtaNi0rcdcIcCRySfYFVtCfoD/ns0T3h1srhwDlhOZ1TSJIQjBZSFfaKHxA7AEWYAXQAEeIWpKVrhVnG7hfsEOxeQU3AAPmcisP8fjINTVP6d9gY34tmXiVCJQ/2J+4AvQEJAQFvqYdOoWYAUT7VgAxDfMDnxiW6HPsQCLQW1uC7CZvh8Sg4bWKDBoRG3XBF0U+AEcxxlsADhc2GzbYE0uuBE03cDmFo9MbBS0TM+0vKjAxElkhL6Dc4h0PBpxizABcbU7ol7ke7a5jd+La1iRwYhrjryIEpt1iRhR3mWuH3lnsAHgcGEzfR7g8E4C0HBNOzD8CDSIdAn+sXwV9WybYXbKwySoMGX63fBN0uWYGA22EvW4xJK7BUcMR0FMG1sDsAEAHGugVXR/YOOjUZPiyMNNVRPzTBtUEPWTd4sMcy3C0PSBVjNsTsf7B0wDOVr2dmYAEHbXF8pLS8mUw4v6mCIrFAbs3Dw3U+ld1zsjsHngCeiIGYKbFp+mAkwy4gBbEVZ4M5DzTYNPsSbpdxC1bcLmcSInSqTx/hA200bYNjFZ5wbCABpk4ARVHnJGYBPoviyMrERz6sjsCL1asTl8BZDqjQKJnboocopMBG0rtQNlNPQMOopvimnhKahRbbdcO3AJC1jZsyZmJmzUXIJN1vQPDzbX9gntsoCyKJRsccqw8cb2mVVsWlUzZGbIg4DZyrNxq8sY8aCA0NzO78VkbGQatAP/CqXiNOgSN4yCbY9oy2lASGlPVBo2+IgfImwGN8EJYMeaSJ0SRNg2w/qCXbBvjUtx0wAKUBeA2RFOqAPlFM9wqWk2cVBQWdlQw4MKHDJU5PsJqNbArtwI90viQ8BTIFBJ2K5jcykT4NmYyk4KzPZh8g/zgJgKdDERCB/IhCAmI4XKBwJsuCjfY9oTzRWEy40kbCoLKovEXCKhlOGW6q2MI6auzoV1xfQj3DW6QaFyn7uGbR8sQAWHmA9CPZvaruH6IH/MwjQZPaRuF4Sia2OcSci5Cf4nAJC4SUVgMoCKCviASLjQXzEziD2bXAdX8IQpjcMyNU1wki6NF+BHhAsMVoFP4Jccv4WoDjZgk0OQywI/wm0CU64ELzOJgfMMG8eaMLci8GSmKUCMadOHWJAK3zbsQ2oJZ4wFSk3xxmJzigekeAgTcsUo5YJSwSl14Y8heFPYqILNRc9GQVdhOSCAisAiIMxRX+N3zAPPBi4tfktwYeL6OGwK7g52HXAm2ZYbw4fUZBo2WR+xGET1jLkGx36yxIosOWsF1DAoP6ATCVgwAxsAxoAhyrEREGGCm844gAUocAAvQPCWYJPbqWWh/B9Vm6OXZIak1sV3p2+Rusn0Cyr8k6vLjaceNfai5x22wBIhM6wwsnxheBDa+AGz5Dw8xerDe+TZwIHATYaYSvVUMgNGA/QsHPkgsBwgeEghLNJJymMBNvRb8kPXkL4PmREKNvk5eD9851H1NvBQRuNKSaD8lyoI3+A2INGe3ImGjY9MMqLYc0x0pWZCZdgMySHCxikBuoA4FtcX0K/BHzKF2EFFVfokjMeYfIEg31uATSjBk8sunYeNKbrkO2/q2WDHgdzSm8AmS/OUZ5OwudqzqZDWtu2RxbDBSeb7DKhcWt2IjfjhdcpmFOuadNJEhgGTF8TwAGcuCCSCB7CYREjwGGWqNgqrclgf3VTAhcCYDaq2FGO2CWwYm3EsDShmKIzxW0GwfuoSWRR8wwVAqjbWsC2nDLoQs4XkdE67IDREGJEtJerWWh8NQDfdaQJNVjllUgwcFtY5ledRgT+qGyypPBvD6iOl0usBixwIwf+I8m4CM2vAIXwDtUoPddOL3yJHlErFpJ78BsO0eGMJG9GwzWWW4edp+qcdNJiNHs8/wKfoPMFPvbHALDNnCj7GABemujYQhoLIsBsgvMAaHrY9MFyAPzSBUb9c24s3lFkzxmS+TGDaXG4i021M/otFyVVwK67+kXuV5ctvNWx4iyRyM+8XPziH0YVJN5aR1t3CtS3C5mrYtG2pZhto2LRtK7TYXLuuhk3b1kzDpk3Dpk3Dpk1bZfv/MDSKiB+3fjYAAAAASUVORK5CYII="
}
},
"cell_type": "markdown",
"metadata": {},
"source": [
"À l'aide de cette image, on peut déterminer la focale nécessaire pour l'appareil photo.\n",
"\n",
"![angle-de-champ-par-focale-en-24x36-1.png.png](attachment:angle-de-champ-par-focale-en-24x36-1.png.png)\n",
"\n",
"On en déduit que la focale de l'objectif devrait être comprise entre 100 et 75 mm."
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"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": "3.10.7"
},
"orig_nbformat": 4
},
"nbformat": 4,
"nbformat_minor": 2
}
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