diff --git a/.ipynb_checkpoints/CameraCalibration-checkpoint.ipynb b/.ipynb_checkpoints/CameraCalibration-checkpoint.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..9fa3bbe9119284a0bb75236a837087385bbee808
--- /dev/null
+++ b/.ipynb_checkpoints/CameraCalibration-checkpoint.ipynb
@@ -0,0 +1,728 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 35,
+ "id": "2a7d76f9-118d-495f-bce1-8d502caa3f4d",
+ "metadata": {},
+ "outputs": [
+ {
+ "ename": "error",
+ "evalue": "OpenCV(4.5.5) /Users/runner/miniforge3/conda-bld/libopencv_1648505779078/work/modules/calib3d/src/calibration.cpp:3694: error: (-215:Assertion failed) nimages > 0 in function 'calibrateCameraRO'\n",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+ "\u001b[0;31merror\u001b[0m Traceback (most recent call last)",
+ "\u001b[0;32m<ipython-input-35-f93f09ea17d7>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 66\u001b[0m \u001b[0mdetected\u001b[0m \u001b[0mcorners\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mimgpoints\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 67\u001b[0m \"\"\"\n\u001b[0;32m---> 68\u001b[0;31m \u001b[0mret\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmtx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdist\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrvecs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtvecs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcv2\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcalibrateCamera\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobjpoints\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mimgpoints\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mgray\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 69\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 70\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Camera matrix : \\n\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;31merror\u001b[0m: OpenCV(4.5.5) /Users/runner/miniforge3/conda-bld/libopencv_1648505779078/work/modules/calib3d/src/calibration.cpp:3694: error: (-215:Assertion failed) nimages > 0 in function 'calibrateCameraRO'\n"
+ ]
+ }
+ ],
+ "source": [
+ "import cv2\n",
+ "import numpy as np\n",
+ "import os\n",
+ "import glob\n",
+ "\n",
+ "# Defining the dimensions of checkerboard\n",
+ "CHECKERBOARD = (6,9)\n",
+ "criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001)\n",
+ "\n",
+ "# Creating vector to store vectors of 3D points for each checkerboard image\n",
+ "objpoints = []\n",
+ "# Creating vector to store vectors of 2D points for each checkerboard image\n",
+ "imgpoints = [] \n",
+ "\n",
+ "\n",
+ "# Defining the world coordinates for 3D points\n",
+ "objp = np.zeros((1, CHECKERBOARD[0] * CHECKERBOARD[1], 3), np.float32)\n",
+ "objp[0,:,:2] = np.mgrid[0:CHECKERBOARD[0], 0:CHECKERBOARD[1]].T.reshape(-1, 2)\n",
+ "prev_img_shape = None\n",
+ "\n",
+ "# Extracting path of individual image stored in a given directory\n",
+ "images = glob.glob('./images/*.jpg')\n",
+ "a = 1\n",
+ "for fname in images:\n",
+ " print(\"Load images\")\n",
+ " img = cv2.imread(fname)\n",
+ " gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)\n",
+ " # Find the chess board corners\n",
+ " # If desired number of corners are found in the image then ret = true\n",
+ " print(\"Finding chessboard corners\")\n",
+ " ret, corners = cv2.findChessboardCorners(gray, CHECKERBOARD, cv2.CALIB_CB_ADAPTIVE_THRESH + cv2.CALIB_CB_FAST_CHECK + cv2.CALIB_CB_NORMALIZE_IMAGE)\n",
+ " \n",
+ " print(\"corners \\n\")\n",
+ " print(corners)\n",
+ " print(\"ret \\n\")\n",
+ " print(ret)\n",
+ " \n",
+ " \"\"\"\n",
+ " If desired number of corner are detected,\n",
+ " we refine the pixel coordinates and display \n",
+ " them on the images of checker board\n",
+ " \"\"\"\n",
+ " if ret == True:\n",
+ " print(\"Corners detected\")\n",
+ " objpoints.append(objp)\n",
+ " # refining pixel coordinates for given 2d points.\n",
+ " corners2 = cv2.cornerSubPix(gray, corners, (11,11),(-1,-1), criteria)\n",
+ " \n",
+ " imgpoints.append(corners2)\n",
+ "\n",
+ " # Draw and display the corners\n",
+ " img = cv2.drawChessboardCorners(img, CHECKERBOARD, corners2, ret)\n",
+ " \n",
+ " print(\"Show images\")\n",
+ " # cv2.imshow('img',img)\n",
+ " nome='foto_processada' + str(a) + '.jpg'\n",
+ " cv2.imwrite(nome, img)\n",
+ " a+=1\n",
+ "\n",
+ "h,w = img.shape[:2]\n",
+ "\n",
+ "\"\"\"\n",
+ "Performing camera calibration by \n",
+ "passing the value of known 3D points (objpoints)\n",
+ "and corresponding pixel coordinates of the \n",
+ "detected corners (imgpoints)\n",
+ "\"\"\"\n",
+ "ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera(objpoints, imgpoints, gray.shape[::-1], None, None)\n",
+ "\n",
+ "print(\"Camera matrix : \\n\")\n",
+ "print(mtx)\n",
+ "print(\"dist : \\n\")\n",
+ "print(dist)\n",
+ "print(\"rvecs : \\n\")\n",
+ "print(rvecs)\n",
+ "print(\"tvecs : \\n\")\n",
+ "print(tvecs)\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 44,
+ "id": "ff6380f6-b96f-469c-bd7f-17fbb3721389",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Load images\n",
+ "Finding chessboard corners\n",
+ "corners \n",
+ "\n",
+ "[[[142.64168 254.9432 ]]\n",
+ "\n",
+ " [[146.75854 225.61407 ]]\n",
+ "\n",
+ " [[150.54066 196.51573 ]]\n",
+ "\n",
+ " [[154.04866 167.27895 ]]\n",
+ "\n",
+ " [[157.64587 138.57889 ]]\n",
+ "\n",
+ " [[161.52353 110.188255]]\n",
+ "\n",
+ " [[173.47812 258.40778 ]]\n",
+ "\n",
+ " [[176.93672 229.4982 ]]\n",
+ "\n",
+ " [[180.49413 200.70557 ]]\n",
+ "\n",
+ " [[184.05624 171.98401 ]]\n",
+ "\n",
+ " [[187.66382 144.17943 ]]\n",
+ "\n",
+ " [[190.79807 116.24408 ]]\n",
+ "\n",
+ " [[203.03679 261.4418 ]]\n",
+ "\n",
+ " [[206.62283 232.9877 ]]\n",
+ "\n",
+ " [[209.51048 204.94817 ]]\n",
+ "\n",
+ " [[212.91487 176.95428 ]]\n",
+ "\n",
+ " [[216.23514 149.11143 ]]\n",
+ "\n",
+ " [[219.46265 121.66086 ]]\n",
+ "\n",
+ " [[231.7584 264.68643 ]]\n",
+ "\n",
+ " [[234.71873 236.5048 ]]\n",
+ "\n",
+ " [[237.93755 209.0442 ]]\n",
+ "\n",
+ " [[241.19179 181.42677 ]]\n",
+ "\n",
+ " [[243.81526 154.10678 ]]\n",
+ "\n",
+ " [[246.94101 126.50662 ]]\n",
+ "\n",
+ " [[259.238 267.7193 ]]\n",
+ "\n",
+ " [[262.34668 240.02777 ]]\n",
+ "\n",
+ " [[265.4873 213.02408 ]]\n",
+ "\n",
+ " [[268.29196 185.80069 ]]\n",
+ "\n",
+ " [[271.08856 158.79974 ]]\n",
+ "\n",
+ " [[274.03 131.71118 ]]\n",
+ "\n",
+ " [[285.894 270.6857 ]]\n",
+ "\n",
+ " [[288.91974 243.85074 ]]\n",
+ "\n",
+ " [[291.67294 216.57468 ]]\n",
+ "\n",
+ " [[294.623 189.9902 ]]\n",
+ "\n",
+ " [[297.21625 163.05467 ]]\n",
+ "\n",
+ " [[300.24863 136.88556 ]]\n",
+ "\n",
+ " [[312.1065 273.9727 ]]\n",
+ "\n",
+ " [[314.64572 246.71307 ]]\n",
+ "\n",
+ " [[317.157 220.33134 ]]\n",
+ "\n",
+ " [[320.10812 193.81598 ]]\n",
+ "\n",
+ " [[322.75974 167.55089 ]]\n",
+ "\n",
+ " [[325.6024 141.55737 ]]\n",
+ "\n",
+ " [[336.9503 276.28848 ]]\n",
+ "\n",
+ " [[339.49103 249.95747 ]]\n",
+ "\n",
+ " [[341.7496 224.4254 ]]\n",
+ "\n",
+ " [[344.58643 197.6241 ]]\n",
+ "\n",
+ " [[347.26367 172.06337 ]]\n",
+ "\n",
+ " [[350.02148 146.011 ]]\n",
+ "\n",
+ " [[361.31314 279.1676 ]]\n",
+ "\n",
+ " [[363.75967 252.91393 ]]\n",
+ "\n",
+ " [[365.80142 227.11314 ]]\n",
+ "\n",
+ " [[368.71347 201.5229 ]]\n",
+ "\n",
+ " [[371.02176 176.04767 ]]\n",
+ "\n",
+ " [[373.48065 150.7466 ]]]\n",
+ "ret \n",
+ "\n",
+ "True\n",
+ "Corners detected\n",
+ "Show images\n",
+ "Load images\n",
+ "Finding chessboard corners\n",
+ "corners \n",
+ "\n",
+ "[[[290.16937 306.88214]]\n",
+ "\n",
+ " [[290.53278 280.11667]]\n",
+ "\n",
+ " [[290.77576 252.93272]]\n",
+ "\n",
+ " [[291.0845 225.27896]]\n",
+ "\n",
+ " [[291.53607 197.0897 ]]\n",
+ "\n",
+ " [[292.41327 168.24815]]\n",
+ "\n",
+ " [[315.06952 311.0208 ]]\n",
+ "\n",
+ " [[315.6739 283.6647 ]]\n",
+ "\n",
+ " [[316.2393 256.1716 ]]\n",
+ "\n",
+ " [[316.59756 227.64337]]\n",
+ "\n",
+ " [[317.8294 198.79442]]\n",
+ "\n",
+ " [[318.80643 169.55096]]\n",
+ "\n",
+ " [[340.638 315.39575]]\n",
+ "\n",
+ " [[341.63934 287.54718]]\n",
+ "\n",
+ " [[342.54242 259.35623]]\n",
+ "\n",
+ " [[343.91376 230.37785]]\n",
+ "\n",
+ " [[345.06934 201.05199]]\n",
+ "\n",
+ " [[346.2913 171.26308]]\n",
+ "\n",
+ " [[367.9363 319.6347 ]]\n",
+ "\n",
+ " [[368.97598 291.21472]]\n",
+ "\n",
+ " [[370.40988 262.52164]]\n",
+ "\n",
+ " [[371.5862 233.02112]]\n",
+ "\n",
+ " [[373.30624 203.30626]]\n",
+ "\n",
+ " [[374.47787 172.69196]]\n",
+ "\n",
+ " [[396.0801 324.31546]]\n",
+ "\n",
+ " [[397.2893 295.3254 ]]\n",
+ "\n",
+ " [[398.77914 265.93915]]\n",
+ "\n",
+ " [[400.4216 236.04366]]\n",
+ "\n",
+ " [[402.11496 205.60799]]\n",
+ "\n",
+ " [[403.97397 174.59514]]\n",
+ "\n",
+ " [[425.58887 328.73993]]\n",
+ "\n",
+ " [[427.1569 299.32626]]\n",
+ "\n",
+ " [[428.80847 269.61078]]\n",
+ "\n",
+ " [[430.6196 238.81488]]\n",
+ "\n",
+ " [[432.5938 207.88199]]\n",
+ "\n",
+ " [[434.81232 176.30792]]\n",
+ "\n",
+ " [[456.30505 333.57922]]\n",
+ "\n",
+ " [[458.36752 303.69302]]\n",
+ "\n",
+ " [[460.31778 273.17523]]\n",
+ "\n",
+ " [[462.44522 242.11354]]\n",
+ "\n",
+ " [[464.63388 210.30637]]\n",
+ "\n",
+ " [[467.06512 178.04515]]\n",
+ "\n",
+ " [[488.32422 338.7988 ]]\n",
+ "\n",
+ " [[490.48627 308.26813]]\n",
+ "\n",
+ " [[492.9652 276.772 ]]\n",
+ "\n",
+ " [[495.6021 245.111 ]]\n",
+ "\n",
+ " [[498.3957 212.66432]]\n",
+ "\n",
+ " [[501.15192 179.73419]]\n",
+ "\n",
+ " [[521.8725 344.20172]]\n",
+ "\n",
+ " [[524.48047 312.59525]]\n",
+ "\n",
+ " [[527.2914 281.0416 ]]\n",
+ "\n",
+ " [[530.3484 248.3829 ]]\n",
+ "\n",
+ " [[533.45984 215.4207 ]]\n",
+ "\n",
+ " [[536.5843 181.58168]]]\n",
+ "ret \n",
+ "\n",
+ "True\n",
+ "Corners detected\n",
+ "Show images\n",
+ "Load images\n",
+ "Finding chessboard corners\n",
+ "corners \n",
+ "\n",
+ "[[[181.65076 240.43515 ]]\n",
+ "\n",
+ " [[182.98524 216.97383 ]]\n",
+ "\n",
+ " [[184.64604 192.23103 ]]\n",
+ "\n",
+ " [[186.13664 165.44173 ]]\n",
+ "\n",
+ " [[187.51831 136.71654 ]]\n",
+ "\n",
+ " [[188.62773 106.87892 ]]\n",
+ "\n",
+ " [[209.48434 240.83936 ]]\n",
+ "\n",
+ " [[211.59288 217.80495 ]]\n",
+ "\n",
+ " [[213.6713 193.07858 ]]\n",
+ "\n",
+ " [[215.5483 166.35489 ]]\n",
+ "\n",
+ " [[217.48494 138.31812 ]]\n",
+ "\n",
+ " [[219.43669 108.85271 ]]\n",
+ "\n",
+ " [[236.70854 241.51544 ]]\n",
+ "\n",
+ " [[239.46967 218.49294 ]]\n",
+ "\n",
+ " [[241.6721 194.00006 ]]\n",
+ "\n",
+ " [[244.1657 167.18895 ]]\n",
+ "\n",
+ " [[246.48727 139.78937 ]]\n",
+ "\n",
+ " [[249.17108 111.17387 ]]\n",
+ "\n",
+ " [[263.09882 241.98895 ]]\n",
+ "\n",
+ " [[266.31976 218.94453 ]]\n",
+ "\n",
+ " [[269.2836 194.60536 ]]\n",
+ "\n",
+ " [[272.11176 168.56544 ]]\n",
+ "\n",
+ " [[275.07178 141.52344 ]]\n",
+ "\n",
+ " [[278.2868 113.34714 ]]\n",
+ "\n",
+ " [[288.6269 242.41682 ]]\n",
+ "\n",
+ " [[292.33762 219.4731 ]]\n",
+ "\n",
+ " [[295.634 195.30553 ]]\n",
+ "\n",
+ " [[299.0187 169.72737 ]]\n",
+ "\n",
+ " [[302.50778 143.14719 ]]\n",
+ "\n",
+ " [[306.42252 115.552376]]\n",
+ "\n",
+ " [[313.5622 242.52242 ]]\n",
+ "\n",
+ " [[317.43845 219.64905 ]]\n",
+ "\n",
+ " [[321.32867 195.67903 ]]\n",
+ "\n",
+ " [[325.13644 170.68053 ]]\n",
+ "\n",
+ " [[329.4506 144.55687 ]]\n",
+ "\n",
+ " [[333.65683 117.407425]]\n",
+ "\n",
+ " [[337.9189 242.53233 ]]\n",
+ "\n",
+ " [[342.0708 219.9899 ]]\n",
+ "\n",
+ " [[346.30737 196.3446 ]]\n",
+ "\n",
+ " [[350.5993 171.67969 ]]\n",
+ "\n",
+ " [[355.18494 146.09834 ]]\n",
+ "\n",
+ " [[360.2282 119.398865]]\n",
+ "\n",
+ " [[361.50598 242.38771 ]]\n",
+ "\n",
+ " [[365.82083 220.18697 ]]\n",
+ "\n",
+ " [[370.56412 196.69379 ]]\n",
+ "\n",
+ " [[375.1744 172.38173 ]]\n",
+ "\n",
+ " [[380.44196 147.4049 ]]\n",
+ "\n",
+ " [[386.07758 121.229385]]\n",
+ "\n",
+ " [[384.24615 242.4664 ]]\n",
+ "\n",
+ " [[389.10178 220.35866 ]]\n",
+ "\n",
+ " [[394.30902 197.43806 ]]\n",
+ "\n",
+ " [[399.71222 173.47057 ]]\n",
+ "\n",
+ " [[405.3322 148.5755 ]]\n",
+ "\n",
+ " [[411.4092 122.746666]]]\n",
+ "ret \n",
+ "\n",
+ "True\n",
+ "Corners detected\n",
+ "Show images\n",
+ "Load images\n",
+ "Finding chessboard corners\n",
+ "corners \n",
+ "\n",
+ "[[[287.53036 361.7949 ]]\n",
+ "\n",
+ " [[282.58374 342.85358]]\n",
+ "\n",
+ " [[278.01462 325.26227]]\n",
+ "\n",
+ " [[272.65985 307.25195]]\n",
+ "\n",
+ " [[268.46243 289.60532]]\n",
+ "\n",
+ " [[263.20535 271.30942]]\n",
+ "\n",
+ " [[305.57693 356.4085 ]]\n",
+ "\n",
+ " [[300.56805 337.95624]]\n",
+ "\n",
+ " [[295.50082 319.71555]]\n",
+ "\n",
+ " [[290.40643 301.90472]]\n",
+ "\n",
+ " [[285.50308 284.46655]]\n",
+ "\n",
+ " [[281.19418 267.06412]]\n",
+ "\n",
+ " [[323.32886 351.0642 ]]\n",
+ "\n",
+ " [[318.34674 332.87128]]\n",
+ "\n",
+ " [[313.38998 314.55502]]\n",
+ "\n",
+ " [[307.87402 296.82272]]\n",
+ "\n",
+ " [[303.11688 279.44043]]\n",
+ "\n",
+ " [[298.32162 261.79645]]\n",
+ "\n",
+ " [[340.5354 345.56195]]\n",
+ "\n",
+ " [[335.7001 327.50388]]\n",
+ "\n",
+ " [[330.57962 310.177 ]]\n",
+ "\n",
+ " [[325.31915 292.1104 ]]\n",
+ "\n",
+ " [[320.627 274.28772]]\n",
+ "\n",
+ " [[315.36737 257.47568]]\n",
+ "\n",
+ " [[358.15817 340.35425]]\n",
+ "\n",
+ " [[352.91727 322.5884 ]]\n",
+ "\n",
+ " [[347.64328 304.45084]]\n",
+ "\n",
+ " [[342.7978 287.11328]]\n",
+ "\n",
+ " [[337.47632 269.54434]]\n",
+ "\n",
+ " [[332.27792 253.0178 ]]\n",
+ "\n",
+ " [[375.521 334.54907]]\n",
+ "\n",
+ " [[370.54572 317.49283]]\n",
+ "\n",
+ " [[365.13348 300.1963 ]]\n",
+ "\n",
+ " [[359.96573 282.50775]]\n",
+ "\n",
+ " [[354.63464 264.84613]]\n",
+ "\n",
+ " [[349.94232 247.95018]]\n",
+ "\n",
+ " [[392.5023 330.13177]]\n",
+ "\n",
+ " [[387.49005 312.34338]]\n",
+ "\n",
+ " [[381.98724 294.8061 ]]\n",
+ "\n",
+ " [[376.97012 277.55432]]\n",
+ "\n",
+ " [[371.30545 260.40204]]\n",
+ "\n",
+ " [[366.55707 243.28087]]\n",
+ "\n",
+ " [[409.58173 325.1956 ]]\n",
+ "\n",
+ " [[404.145 307.3832 ]]\n",
+ "\n",
+ " [[398.70715 289.91235]]\n",
+ "\n",
+ " [[393.5826 272.64722]]\n",
+ "\n",
+ " [[388.28845 255.7331 ]]\n",
+ "\n",
+ " [[384.17352 239.4941 ]]\n",
+ "\n",
+ " [[426.2251 320.06195]]\n",
+ "\n",
+ " [[420.66238 302.5737 ]]\n",
+ "\n",
+ " [[414.9943 284.84647]]\n",
+ "\n",
+ " [[410.52255 267.81345]]\n",
+ "\n",
+ " [[405.14496 251.26006]]\n",
+ "\n",
+ " [[400.21164 234.16982]]]\n",
+ "ret \n",
+ "\n",
+ "True\n",
+ "Corners detected\n",
+ "Show images\n",
+ "Camera matrix : \n",
+ "\n",
+ "[[603.52572321 0. 326.41229818]\n",
+ " [ 0. 603.65899926 235.9537242 ]\n",
+ " [ 0. 0. 1. ]]\n",
+ "dist : \n",
+ "\n",
+ "[[ 1.78080527e-01 -1.34103119e+00 -4.51376510e-03 2.52476784e-03\n",
+ " 4.71440744e+00]]\n",
+ "rvecs : \n",
+ "\n",
+ "(array([[ 0.19951224],\n",
+ " [-0.31463841],\n",
+ " [-1.43904688]]), array([[-0.19044869],\n",
+ " [ 0.44388641],\n",
+ " [-1.47868386]]), array([[ 0.61618287],\n",
+ " [ 0.13666227],\n",
+ " [-1.44098723]]), array([[ 0.01147331],\n",
+ " [-0.24455644],\n",
+ " [-1.83474358]]))\n",
+ "tvecs : \n",
+ "\n",
+ "(array([[-6.18074691],\n",
+ " [ 0.64577552],\n",
+ " [20.4775399 ]]), array([[-1.33022191],\n",
+ " [ 2.5755565 ],\n",
+ " [21.87116664]]), array([[-5.25095778],\n",
+ " [ 0.22170776],\n",
+ " [22.06269285]]), array([[-2.0724692 ],\n",
+ " [ 6.70679783],\n",
+ " [32.30219442]]))\n"
+ ]
+ }
+ ],
+ "source": [
+ "import cv2\n",
+ "import numpy as np\n",
+ "import os\n",
+ "import glob\n",
+ "\n",
+ "# Defining the dimensions of checkerboard\n",
+ "CHECKERBOARD = (6,9)\n",
+ "criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001)\n",
+ "\n",
+ "# Creating vector to store vectors of 3D points for each checkerboard image\n",
+ "objpoints = []\n",
+ "# Creating vector to store vectors of 2D points for each checkerboard image\n",
+ "imgpoints = [] \n",
+ "\n",
+ "\n",
+ "# Defining the world coordinates for 3D points\n",
+ "objp = np.zeros((1, CHECKERBOARD[0] * CHECKERBOARD[1], 3), np.float32)\n",
+ "objp[0,:,:2] = np.mgrid[0:CHECKERBOARD[0], 0:CHECKERBOARD[1]].T.reshape(-1, 2)\n",
+ "prev_img_shape = None\n",
+ "\n",
+ "# Extracting path of individual image stored in a given directory\n",
+ "images = glob.glob('./images/*.jpeg')\n",
+ "a = 1\n",
+ "for fname in images:\n",
+ " print(\"Load images\")\n",
+ " img = cv2.imread(fname)\n",
+ " gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)\n",
+ " # Find the chess board corners\n",
+ " # If desired number of corners are found in the image then ret = true\n",
+ " print(\"Finding chessboard corners\")\n",
+ " ret, corners = cv2.findChessboardCorners(gray, CHECKERBOARD, None)\n",
+ " \n",
+ " print(\"corners \\n\")\n",
+ " print(corners)\n",
+ " print(\"ret \\n\")\n",
+ " print(ret)\n",
+ " \n",
+ " \"\"\"\n",
+ " If desired number of corner are detected,\n",
+ " we refine the pixel coordinates and display \n",
+ " them on the images of checker board\n",
+ " \"\"\"\n",
+ " if ret == True:\n",
+ " print(\"Corners detected\")\n",
+ " objpoints.append(objp)\n",
+ " # refining pixel coordinates for given 2d points.\n",
+ " corners2 = cv2.cornerSubPix(gray, corners, (11,11),(-1,-1), criteria)\n",
+ " \n",
+ " imgpoints.append(corners2)\n",
+ "\n",
+ " # Draw and display the corners\n",
+ " img = cv2.drawChessboardCorners(img, CHECKERBOARD, corners2, ret)\n",
+ " \n",
+ " print(\"Show images\")\n",
+ " # cv2.imshow('img',img)\n",
+ " nome='foto_processada' + str(a) + '.jpg'\n",
+ " cv2.imwrite(nome, img)\n",
+ " a+=1\n",
+ "\n",
+ "h,w = img.shape[:2]\n",
+ "\n",
+ "\"\"\"\n",
+ "Performing camera calibration by \n",
+ "passing the value of known 3D points (objpoints)\n",
+ "and corresponding pixel coordinates of the \n",
+ "detected corners (imgpoints)\n",
+ "\"\"\"\n",
+ "ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera(objpoints, imgpoints, gray.shape[::-1], None, None)\n",
+ "\n",
+ "print(\"Camera matrix : \\n\")\n",
+ "print(mtx)\n",
+ "print(\"dist : \\n\")\n",
+ "print(dist)\n",
+ "print(\"rvecs : \\n\")\n",
+ "print(rvecs)\n",
+ "print(\"tvecs : \\n\")\n",
+ "print(tvecs)\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "f1dd04b0-6ae7-49a6-bb70-9dbb9adbc5c4",
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3.8.8 64-bit ('base': conda)",
+ "language": "python",
+ "name": "python388jvsc74a57bd031c25f6a857731a2f8662034dc52be9f81dff2f8cc48f1a86bd9478e5f7d5ada"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.8.13"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/.ipynb_checkpoints/foto_processada1-checkpoint.jpg b/.ipynb_checkpoints/foto_processada1-checkpoint.jpg
new file mode 100644
index 0000000000000000000000000000000000000000..7ed0f1eaca18a074feff6ee524b607212c9cfe76
Binary files /dev/null and b/.ipynb_checkpoints/foto_processada1-checkpoint.jpg differ
diff --git a/.ipynb_checkpoints/foto_processada2-checkpoint.jpg b/.ipynb_checkpoints/foto_processada2-checkpoint.jpg
new file mode 100644
index 0000000000000000000000000000000000000000..0c3e9a59dfe242b66c361ed18e8088ea72261a6c
Binary files /dev/null and b/.ipynb_checkpoints/foto_processada2-checkpoint.jpg differ
diff --git a/.ipynb_checkpoints/foto_processada3-checkpoint.jpg b/.ipynb_checkpoints/foto_processada3-checkpoint.jpg
new file mode 100644
index 0000000000000000000000000000000000000000..c9b30ea4ae5247821a4a69e626586d288d3e08c7
Binary files /dev/null and b/.ipynb_checkpoints/foto_processada3-checkpoint.jpg differ
diff --git a/.ipynb_checkpoints/foto_processada4-checkpoint.jpg b/.ipynb_checkpoints/foto_processada4-checkpoint.jpg
new file mode 100644
index 0000000000000000000000000000000000000000..6be4de0669aac0b7dc5f6bfc403bacb4680d85d9
Binary files /dev/null and b/.ipynb_checkpoints/foto_processada4-checkpoint.jpg differ
diff --git a/CameraCalibration.ipynb b/CameraCalibration.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..9fa3bbe9119284a0bb75236a837087385bbee808
--- /dev/null
+++ b/CameraCalibration.ipynb
@@ -0,0 +1,728 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 35,
+ "id": "2a7d76f9-118d-495f-bce1-8d502caa3f4d",
+ "metadata": {},
+ "outputs": [
+ {
+ "ename": "error",
+ "evalue": "OpenCV(4.5.5) /Users/runner/miniforge3/conda-bld/libopencv_1648505779078/work/modules/calib3d/src/calibration.cpp:3694: error: (-215:Assertion failed) nimages > 0 in function 'calibrateCameraRO'\n",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+ "\u001b[0;31merror\u001b[0m Traceback (most recent call last)",
+ "\u001b[0;32m<ipython-input-35-f93f09ea17d7>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 66\u001b[0m \u001b[0mdetected\u001b[0m \u001b[0mcorners\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mimgpoints\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 67\u001b[0m \"\"\"\n\u001b[0;32m---> 68\u001b[0;31m \u001b[0mret\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmtx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdist\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrvecs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtvecs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcv2\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcalibrateCamera\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobjpoints\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mimgpoints\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mgray\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 69\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 70\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Camera matrix : \\n\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;31merror\u001b[0m: OpenCV(4.5.5) /Users/runner/miniforge3/conda-bld/libopencv_1648505779078/work/modules/calib3d/src/calibration.cpp:3694: error: (-215:Assertion failed) nimages > 0 in function 'calibrateCameraRO'\n"
+ ]
+ }
+ ],
+ "source": [
+ "import cv2\n",
+ "import numpy as np\n",
+ "import os\n",
+ "import glob\n",
+ "\n",
+ "# Defining the dimensions of checkerboard\n",
+ "CHECKERBOARD = (6,9)\n",
+ "criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001)\n",
+ "\n",
+ "# Creating vector to store vectors of 3D points for each checkerboard image\n",
+ "objpoints = []\n",
+ "# Creating vector to store vectors of 2D points for each checkerboard image\n",
+ "imgpoints = [] \n",
+ "\n",
+ "\n",
+ "# Defining the world coordinates for 3D points\n",
+ "objp = np.zeros((1, CHECKERBOARD[0] * CHECKERBOARD[1], 3), np.float32)\n",
+ "objp[0,:,:2] = np.mgrid[0:CHECKERBOARD[0], 0:CHECKERBOARD[1]].T.reshape(-1, 2)\n",
+ "prev_img_shape = None\n",
+ "\n",
+ "# Extracting path of individual image stored in a given directory\n",
+ "images = glob.glob('./images/*.jpg')\n",
+ "a = 1\n",
+ "for fname in images:\n",
+ " print(\"Load images\")\n",
+ " img = cv2.imread(fname)\n",
+ " gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)\n",
+ " # Find the chess board corners\n",
+ " # If desired number of corners are found in the image then ret = true\n",
+ " print(\"Finding chessboard corners\")\n",
+ " ret, corners = cv2.findChessboardCorners(gray, CHECKERBOARD, cv2.CALIB_CB_ADAPTIVE_THRESH + cv2.CALIB_CB_FAST_CHECK + cv2.CALIB_CB_NORMALIZE_IMAGE)\n",
+ " \n",
+ " print(\"corners \\n\")\n",
+ " print(corners)\n",
+ " print(\"ret \\n\")\n",
+ " print(ret)\n",
+ " \n",
+ " \"\"\"\n",
+ " If desired number of corner are detected,\n",
+ " we refine the pixel coordinates and display \n",
+ " them on the images of checker board\n",
+ " \"\"\"\n",
+ " if ret == True:\n",
+ " print(\"Corners detected\")\n",
+ " objpoints.append(objp)\n",
+ " # refining pixel coordinates for given 2d points.\n",
+ " corners2 = cv2.cornerSubPix(gray, corners, (11,11),(-1,-1), criteria)\n",
+ " \n",
+ " imgpoints.append(corners2)\n",
+ "\n",
+ " # Draw and display the corners\n",
+ " img = cv2.drawChessboardCorners(img, CHECKERBOARD, corners2, ret)\n",
+ " \n",
+ " print(\"Show images\")\n",
+ " # cv2.imshow('img',img)\n",
+ " nome='foto_processada' + str(a) + '.jpg'\n",
+ " cv2.imwrite(nome, img)\n",
+ " a+=1\n",
+ "\n",
+ "h,w = img.shape[:2]\n",
+ "\n",
+ "\"\"\"\n",
+ "Performing camera calibration by \n",
+ "passing the value of known 3D points (objpoints)\n",
+ "and corresponding pixel coordinates of the \n",
+ "detected corners (imgpoints)\n",
+ "\"\"\"\n",
+ "ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera(objpoints, imgpoints, gray.shape[::-1], None, None)\n",
+ "\n",
+ "print(\"Camera matrix : \\n\")\n",
+ "print(mtx)\n",
+ "print(\"dist : \\n\")\n",
+ "print(dist)\n",
+ "print(\"rvecs : \\n\")\n",
+ "print(rvecs)\n",
+ "print(\"tvecs : \\n\")\n",
+ "print(tvecs)\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 44,
+ "id": "ff6380f6-b96f-469c-bd7f-17fbb3721389",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Load images\n",
+ "Finding chessboard corners\n",
+ "corners \n",
+ "\n",
+ "[[[142.64168 254.9432 ]]\n",
+ "\n",
+ " [[146.75854 225.61407 ]]\n",
+ "\n",
+ " [[150.54066 196.51573 ]]\n",
+ "\n",
+ " [[154.04866 167.27895 ]]\n",
+ "\n",
+ " [[157.64587 138.57889 ]]\n",
+ "\n",
+ " [[161.52353 110.188255]]\n",
+ "\n",
+ " [[173.47812 258.40778 ]]\n",
+ "\n",
+ " [[176.93672 229.4982 ]]\n",
+ "\n",
+ " [[180.49413 200.70557 ]]\n",
+ "\n",
+ " [[184.05624 171.98401 ]]\n",
+ "\n",
+ " [[187.66382 144.17943 ]]\n",
+ "\n",
+ " [[190.79807 116.24408 ]]\n",
+ "\n",
+ " [[203.03679 261.4418 ]]\n",
+ "\n",
+ " [[206.62283 232.9877 ]]\n",
+ "\n",
+ " [[209.51048 204.94817 ]]\n",
+ "\n",
+ " [[212.91487 176.95428 ]]\n",
+ "\n",
+ " [[216.23514 149.11143 ]]\n",
+ "\n",
+ " [[219.46265 121.66086 ]]\n",
+ "\n",
+ " [[231.7584 264.68643 ]]\n",
+ "\n",
+ " [[234.71873 236.5048 ]]\n",
+ "\n",
+ " [[237.93755 209.0442 ]]\n",
+ "\n",
+ " [[241.19179 181.42677 ]]\n",
+ "\n",
+ " [[243.81526 154.10678 ]]\n",
+ "\n",
+ " [[246.94101 126.50662 ]]\n",
+ "\n",
+ " [[259.238 267.7193 ]]\n",
+ "\n",
+ " [[262.34668 240.02777 ]]\n",
+ "\n",
+ " [[265.4873 213.02408 ]]\n",
+ "\n",
+ " [[268.29196 185.80069 ]]\n",
+ "\n",
+ " [[271.08856 158.79974 ]]\n",
+ "\n",
+ " [[274.03 131.71118 ]]\n",
+ "\n",
+ " [[285.894 270.6857 ]]\n",
+ "\n",
+ " [[288.91974 243.85074 ]]\n",
+ "\n",
+ " [[291.67294 216.57468 ]]\n",
+ "\n",
+ " [[294.623 189.9902 ]]\n",
+ "\n",
+ " [[297.21625 163.05467 ]]\n",
+ "\n",
+ " [[300.24863 136.88556 ]]\n",
+ "\n",
+ " [[312.1065 273.9727 ]]\n",
+ "\n",
+ " [[314.64572 246.71307 ]]\n",
+ "\n",
+ " [[317.157 220.33134 ]]\n",
+ "\n",
+ " [[320.10812 193.81598 ]]\n",
+ "\n",
+ " [[322.75974 167.55089 ]]\n",
+ "\n",
+ " [[325.6024 141.55737 ]]\n",
+ "\n",
+ " [[336.9503 276.28848 ]]\n",
+ "\n",
+ " [[339.49103 249.95747 ]]\n",
+ "\n",
+ " [[341.7496 224.4254 ]]\n",
+ "\n",
+ " [[344.58643 197.6241 ]]\n",
+ "\n",
+ " [[347.26367 172.06337 ]]\n",
+ "\n",
+ " [[350.02148 146.011 ]]\n",
+ "\n",
+ " [[361.31314 279.1676 ]]\n",
+ "\n",
+ " [[363.75967 252.91393 ]]\n",
+ "\n",
+ " [[365.80142 227.11314 ]]\n",
+ "\n",
+ " [[368.71347 201.5229 ]]\n",
+ "\n",
+ " [[371.02176 176.04767 ]]\n",
+ "\n",
+ " [[373.48065 150.7466 ]]]\n",
+ "ret \n",
+ "\n",
+ "True\n",
+ "Corners detected\n",
+ "Show images\n",
+ "Load images\n",
+ "Finding chessboard corners\n",
+ "corners \n",
+ "\n",
+ "[[[290.16937 306.88214]]\n",
+ "\n",
+ " [[290.53278 280.11667]]\n",
+ "\n",
+ " [[290.77576 252.93272]]\n",
+ "\n",
+ " [[291.0845 225.27896]]\n",
+ "\n",
+ " [[291.53607 197.0897 ]]\n",
+ "\n",
+ " [[292.41327 168.24815]]\n",
+ "\n",
+ " [[315.06952 311.0208 ]]\n",
+ "\n",
+ " [[315.6739 283.6647 ]]\n",
+ "\n",
+ " [[316.2393 256.1716 ]]\n",
+ "\n",
+ " [[316.59756 227.64337]]\n",
+ "\n",
+ " [[317.8294 198.79442]]\n",
+ "\n",
+ " [[318.80643 169.55096]]\n",
+ "\n",
+ " [[340.638 315.39575]]\n",
+ "\n",
+ " [[341.63934 287.54718]]\n",
+ "\n",
+ " [[342.54242 259.35623]]\n",
+ "\n",
+ " [[343.91376 230.37785]]\n",
+ "\n",
+ " [[345.06934 201.05199]]\n",
+ "\n",
+ " [[346.2913 171.26308]]\n",
+ "\n",
+ " [[367.9363 319.6347 ]]\n",
+ "\n",
+ " [[368.97598 291.21472]]\n",
+ "\n",
+ " [[370.40988 262.52164]]\n",
+ "\n",
+ " [[371.5862 233.02112]]\n",
+ "\n",
+ " [[373.30624 203.30626]]\n",
+ "\n",
+ " [[374.47787 172.69196]]\n",
+ "\n",
+ " [[396.0801 324.31546]]\n",
+ "\n",
+ " [[397.2893 295.3254 ]]\n",
+ "\n",
+ " [[398.77914 265.93915]]\n",
+ "\n",
+ " [[400.4216 236.04366]]\n",
+ "\n",
+ " [[402.11496 205.60799]]\n",
+ "\n",
+ " [[403.97397 174.59514]]\n",
+ "\n",
+ " [[425.58887 328.73993]]\n",
+ "\n",
+ " [[427.1569 299.32626]]\n",
+ "\n",
+ " [[428.80847 269.61078]]\n",
+ "\n",
+ " [[430.6196 238.81488]]\n",
+ "\n",
+ " [[432.5938 207.88199]]\n",
+ "\n",
+ " [[434.81232 176.30792]]\n",
+ "\n",
+ " [[456.30505 333.57922]]\n",
+ "\n",
+ " [[458.36752 303.69302]]\n",
+ "\n",
+ " [[460.31778 273.17523]]\n",
+ "\n",
+ " [[462.44522 242.11354]]\n",
+ "\n",
+ " [[464.63388 210.30637]]\n",
+ "\n",
+ " [[467.06512 178.04515]]\n",
+ "\n",
+ " [[488.32422 338.7988 ]]\n",
+ "\n",
+ " [[490.48627 308.26813]]\n",
+ "\n",
+ " [[492.9652 276.772 ]]\n",
+ "\n",
+ " [[495.6021 245.111 ]]\n",
+ "\n",
+ " [[498.3957 212.66432]]\n",
+ "\n",
+ " [[501.15192 179.73419]]\n",
+ "\n",
+ " [[521.8725 344.20172]]\n",
+ "\n",
+ " [[524.48047 312.59525]]\n",
+ "\n",
+ " [[527.2914 281.0416 ]]\n",
+ "\n",
+ " [[530.3484 248.3829 ]]\n",
+ "\n",
+ " [[533.45984 215.4207 ]]\n",
+ "\n",
+ " [[536.5843 181.58168]]]\n",
+ "ret \n",
+ "\n",
+ "True\n",
+ "Corners detected\n",
+ "Show images\n",
+ "Load images\n",
+ "Finding chessboard corners\n",
+ "corners \n",
+ "\n",
+ "[[[181.65076 240.43515 ]]\n",
+ "\n",
+ " [[182.98524 216.97383 ]]\n",
+ "\n",
+ " [[184.64604 192.23103 ]]\n",
+ "\n",
+ " [[186.13664 165.44173 ]]\n",
+ "\n",
+ " [[187.51831 136.71654 ]]\n",
+ "\n",
+ " [[188.62773 106.87892 ]]\n",
+ "\n",
+ " [[209.48434 240.83936 ]]\n",
+ "\n",
+ " [[211.59288 217.80495 ]]\n",
+ "\n",
+ " [[213.6713 193.07858 ]]\n",
+ "\n",
+ " [[215.5483 166.35489 ]]\n",
+ "\n",
+ " [[217.48494 138.31812 ]]\n",
+ "\n",
+ " [[219.43669 108.85271 ]]\n",
+ "\n",
+ " [[236.70854 241.51544 ]]\n",
+ "\n",
+ " [[239.46967 218.49294 ]]\n",
+ "\n",
+ " [[241.6721 194.00006 ]]\n",
+ "\n",
+ " [[244.1657 167.18895 ]]\n",
+ "\n",
+ " [[246.48727 139.78937 ]]\n",
+ "\n",
+ " [[249.17108 111.17387 ]]\n",
+ "\n",
+ " [[263.09882 241.98895 ]]\n",
+ "\n",
+ " [[266.31976 218.94453 ]]\n",
+ "\n",
+ " [[269.2836 194.60536 ]]\n",
+ "\n",
+ " [[272.11176 168.56544 ]]\n",
+ "\n",
+ " [[275.07178 141.52344 ]]\n",
+ "\n",
+ " [[278.2868 113.34714 ]]\n",
+ "\n",
+ " [[288.6269 242.41682 ]]\n",
+ "\n",
+ " [[292.33762 219.4731 ]]\n",
+ "\n",
+ " [[295.634 195.30553 ]]\n",
+ "\n",
+ " [[299.0187 169.72737 ]]\n",
+ "\n",
+ " [[302.50778 143.14719 ]]\n",
+ "\n",
+ " [[306.42252 115.552376]]\n",
+ "\n",
+ " [[313.5622 242.52242 ]]\n",
+ "\n",
+ " [[317.43845 219.64905 ]]\n",
+ "\n",
+ " [[321.32867 195.67903 ]]\n",
+ "\n",
+ " [[325.13644 170.68053 ]]\n",
+ "\n",
+ " [[329.4506 144.55687 ]]\n",
+ "\n",
+ " [[333.65683 117.407425]]\n",
+ "\n",
+ " [[337.9189 242.53233 ]]\n",
+ "\n",
+ " [[342.0708 219.9899 ]]\n",
+ "\n",
+ " [[346.30737 196.3446 ]]\n",
+ "\n",
+ " [[350.5993 171.67969 ]]\n",
+ "\n",
+ " [[355.18494 146.09834 ]]\n",
+ "\n",
+ " [[360.2282 119.398865]]\n",
+ "\n",
+ " [[361.50598 242.38771 ]]\n",
+ "\n",
+ " [[365.82083 220.18697 ]]\n",
+ "\n",
+ " [[370.56412 196.69379 ]]\n",
+ "\n",
+ " [[375.1744 172.38173 ]]\n",
+ "\n",
+ " [[380.44196 147.4049 ]]\n",
+ "\n",
+ " [[386.07758 121.229385]]\n",
+ "\n",
+ " [[384.24615 242.4664 ]]\n",
+ "\n",
+ " [[389.10178 220.35866 ]]\n",
+ "\n",
+ " [[394.30902 197.43806 ]]\n",
+ "\n",
+ " [[399.71222 173.47057 ]]\n",
+ "\n",
+ " [[405.3322 148.5755 ]]\n",
+ "\n",
+ " [[411.4092 122.746666]]]\n",
+ "ret \n",
+ "\n",
+ "True\n",
+ "Corners detected\n",
+ "Show images\n",
+ "Load images\n",
+ "Finding chessboard corners\n",
+ "corners \n",
+ "\n",
+ "[[[287.53036 361.7949 ]]\n",
+ "\n",
+ " [[282.58374 342.85358]]\n",
+ "\n",
+ " [[278.01462 325.26227]]\n",
+ "\n",
+ " [[272.65985 307.25195]]\n",
+ "\n",
+ " [[268.46243 289.60532]]\n",
+ "\n",
+ " [[263.20535 271.30942]]\n",
+ "\n",
+ " [[305.57693 356.4085 ]]\n",
+ "\n",
+ " [[300.56805 337.95624]]\n",
+ "\n",
+ " [[295.50082 319.71555]]\n",
+ "\n",
+ " [[290.40643 301.90472]]\n",
+ "\n",
+ " [[285.50308 284.46655]]\n",
+ "\n",
+ " [[281.19418 267.06412]]\n",
+ "\n",
+ " [[323.32886 351.0642 ]]\n",
+ "\n",
+ " [[318.34674 332.87128]]\n",
+ "\n",
+ " [[313.38998 314.55502]]\n",
+ "\n",
+ " [[307.87402 296.82272]]\n",
+ "\n",
+ " [[303.11688 279.44043]]\n",
+ "\n",
+ " [[298.32162 261.79645]]\n",
+ "\n",
+ " [[340.5354 345.56195]]\n",
+ "\n",
+ " [[335.7001 327.50388]]\n",
+ "\n",
+ " [[330.57962 310.177 ]]\n",
+ "\n",
+ " [[325.31915 292.1104 ]]\n",
+ "\n",
+ " [[320.627 274.28772]]\n",
+ "\n",
+ " [[315.36737 257.47568]]\n",
+ "\n",
+ " [[358.15817 340.35425]]\n",
+ "\n",
+ " [[352.91727 322.5884 ]]\n",
+ "\n",
+ " [[347.64328 304.45084]]\n",
+ "\n",
+ " [[342.7978 287.11328]]\n",
+ "\n",
+ " [[337.47632 269.54434]]\n",
+ "\n",
+ " [[332.27792 253.0178 ]]\n",
+ "\n",
+ " [[375.521 334.54907]]\n",
+ "\n",
+ " [[370.54572 317.49283]]\n",
+ "\n",
+ " [[365.13348 300.1963 ]]\n",
+ "\n",
+ " [[359.96573 282.50775]]\n",
+ "\n",
+ " [[354.63464 264.84613]]\n",
+ "\n",
+ " [[349.94232 247.95018]]\n",
+ "\n",
+ " [[392.5023 330.13177]]\n",
+ "\n",
+ " [[387.49005 312.34338]]\n",
+ "\n",
+ " [[381.98724 294.8061 ]]\n",
+ "\n",
+ " [[376.97012 277.55432]]\n",
+ "\n",
+ " [[371.30545 260.40204]]\n",
+ "\n",
+ " [[366.55707 243.28087]]\n",
+ "\n",
+ " [[409.58173 325.1956 ]]\n",
+ "\n",
+ " [[404.145 307.3832 ]]\n",
+ "\n",
+ " [[398.70715 289.91235]]\n",
+ "\n",
+ " [[393.5826 272.64722]]\n",
+ "\n",
+ " [[388.28845 255.7331 ]]\n",
+ "\n",
+ " [[384.17352 239.4941 ]]\n",
+ "\n",
+ " [[426.2251 320.06195]]\n",
+ "\n",
+ " [[420.66238 302.5737 ]]\n",
+ "\n",
+ " [[414.9943 284.84647]]\n",
+ "\n",
+ " [[410.52255 267.81345]]\n",
+ "\n",
+ " [[405.14496 251.26006]]\n",
+ "\n",
+ " [[400.21164 234.16982]]]\n",
+ "ret \n",
+ "\n",
+ "True\n",
+ "Corners detected\n",
+ "Show images\n",
+ "Camera matrix : \n",
+ "\n",
+ "[[603.52572321 0. 326.41229818]\n",
+ " [ 0. 603.65899926 235.9537242 ]\n",
+ " [ 0. 0. 1. ]]\n",
+ "dist : \n",
+ "\n",
+ "[[ 1.78080527e-01 -1.34103119e+00 -4.51376510e-03 2.52476784e-03\n",
+ " 4.71440744e+00]]\n",
+ "rvecs : \n",
+ "\n",
+ "(array([[ 0.19951224],\n",
+ " [-0.31463841],\n",
+ " [-1.43904688]]), array([[-0.19044869],\n",
+ " [ 0.44388641],\n",
+ " [-1.47868386]]), array([[ 0.61618287],\n",
+ " [ 0.13666227],\n",
+ " [-1.44098723]]), array([[ 0.01147331],\n",
+ " [-0.24455644],\n",
+ " [-1.83474358]]))\n",
+ "tvecs : \n",
+ "\n",
+ "(array([[-6.18074691],\n",
+ " [ 0.64577552],\n",
+ " [20.4775399 ]]), array([[-1.33022191],\n",
+ " [ 2.5755565 ],\n",
+ " [21.87116664]]), array([[-5.25095778],\n",
+ " [ 0.22170776],\n",
+ " [22.06269285]]), array([[-2.0724692 ],\n",
+ " [ 6.70679783],\n",
+ " [32.30219442]]))\n"
+ ]
+ }
+ ],
+ "source": [
+ "import cv2\n",
+ "import numpy as np\n",
+ "import os\n",
+ "import glob\n",
+ "\n",
+ "# Defining the dimensions of checkerboard\n",
+ "CHECKERBOARD = (6,9)\n",
+ "criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001)\n",
+ "\n",
+ "# Creating vector to store vectors of 3D points for each checkerboard image\n",
+ "objpoints = []\n",
+ "# Creating vector to store vectors of 2D points for each checkerboard image\n",
+ "imgpoints = [] \n",
+ "\n",
+ "\n",
+ "# Defining the world coordinates for 3D points\n",
+ "objp = np.zeros((1, CHECKERBOARD[0] * CHECKERBOARD[1], 3), np.float32)\n",
+ "objp[0,:,:2] = np.mgrid[0:CHECKERBOARD[0], 0:CHECKERBOARD[1]].T.reshape(-1, 2)\n",
+ "prev_img_shape = None\n",
+ "\n",
+ "# Extracting path of individual image stored in a given directory\n",
+ "images = glob.glob('./images/*.jpeg')\n",
+ "a = 1\n",
+ "for fname in images:\n",
+ " print(\"Load images\")\n",
+ " img = cv2.imread(fname)\n",
+ " gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)\n",
+ " # Find the chess board corners\n",
+ " # If desired number of corners are found in the image then ret = true\n",
+ " print(\"Finding chessboard corners\")\n",
+ " ret, corners = cv2.findChessboardCorners(gray, CHECKERBOARD, None)\n",
+ " \n",
+ " print(\"corners \\n\")\n",
+ " print(corners)\n",
+ " print(\"ret \\n\")\n",
+ " print(ret)\n",
+ " \n",
+ " \"\"\"\n",
+ " If desired number of corner are detected,\n",
+ " we refine the pixel coordinates and display \n",
+ " them on the images of checker board\n",
+ " \"\"\"\n",
+ " if ret == True:\n",
+ " print(\"Corners detected\")\n",
+ " objpoints.append(objp)\n",
+ " # refining pixel coordinates for given 2d points.\n",
+ " corners2 = cv2.cornerSubPix(gray, corners, (11,11),(-1,-1), criteria)\n",
+ " \n",
+ " imgpoints.append(corners2)\n",
+ "\n",
+ " # Draw and display the corners\n",
+ " img = cv2.drawChessboardCorners(img, CHECKERBOARD, corners2, ret)\n",
+ " \n",
+ " print(\"Show images\")\n",
+ " # cv2.imshow('img',img)\n",
+ " nome='foto_processada' + str(a) + '.jpg'\n",
+ " cv2.imwrite(nome, img)\n",
+ " a+=1\n",
+ "\n",
+ "h,w = img.shape[:2]\n",
+ "\n",
+ "\"\"\"\n",
+ "Performing camera calibration by \n",
+ "passing the value of known 3D points (objpoints)\n",
+ "and corresponding pixel coordinates of the \n",
+ "detected corners (imgpoints)\n",
+ "\"\"\"\n",
+ "ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera(objpoints, imgpoints, gray.shape[::-1], None, None)\n",
+ "\n",
+ "print(\"Camera matrix : \\n\")\n",
+ "print(mtx)\n",
+ "print(\"dist : \\n\")\n",
+ "print(dist)\n",
+ "print(\"rvecs : \\n\")\n",
+ "print(rvecs)\n",
+ "print(\"tvecs : \\n\")\n",
+ "print(tvecs)\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "f1dd04b0-6ae7-49a6-bb70-9dbb9adbc5c4",
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3.8.8 64-bit ('base': conda)",
+ "language": "python",
+ "name": "python388jvsc74a57bd031c25f6a857731a2f8662034dc52be9f81dff2f8cc48f1a86bd9478e5f7d5ada"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.8.13"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
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