Corner tracking.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import cv2\n",
    "import numpy as np\n",
    "import os\n",
    "import glob"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Defining the dimensions of checkerboard(長寬各有多少角點數)\n",
    "CHECKERBOARD = (6,9)\n",
    "\n",
    "# 設置像素角點的參數，停止準則採用最大循環次數(max iter)+最大容忍誤差(eps)為30.00\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(world)\n",
    "objpoints = [] # store 3D points\n",
    "# Creating vector to store vectors of 2D points for each checkerboard image(image)\n",
    "imgpoints = [] # store 2D points\n",
    "\n",
    "# Defining the world coordinates for 3D points(定義世界座標=>描述物體真實的位置)\n",
    "## 產生三維的零矩陣\n",
    "objp = np.zeros((1, CHECKERBOARD[0] * CHECKERBOARD[1], 3), np.float32)\n",
    "## 將世界坐標系建在標定版上，所有的Z點座標都為0，所以只有X、Y需要給予數值\n",
    "objp[0,:,:2] = np.mgrid[0:CHECKERBOARD[0], 0:CHECKERBOARD[1]].T.reshape(-1, 2)\n",
    "prev_img_shape = None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Camera matrix(intrinsic parameter) : \n",
      "\n",
      "[[3.03282800e+03 0.00000000e+00 1.53937659e+03]\n",
      " [0.00000000e+00 3.03018944e+03 2.01631367e+03]\n",
      " [0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
      "dist : \n",
      "\n",
      "[[ 0.03258498 -0.21949084  0.00047211  0.0051064   0.35615065]]\n",
      "rvecs(extrinsic parameter) : \n",
      "\n",
      "(array([[ 0.03870172],\n",
      "       [-0.14377813],\n",
      "       [-0.09575442]]), array([[ 0.1225424 ],\n",
      "       [-0.20455739],\n",
      "       [-0.07649326]]), array([[ 0.20910126],\n",
      "       [-0.17313041],\n",
      "       [-0.07735994]]), array([[ 0.34729888],\n",
      "       [-0.19311932],\n",
      "       [-0.02122464]]), array([[ 0.37139541],\n",
      "       [-0.19295209],\n",
      "       [ 0.03791292]]), array([[ 0.46245695],\n",
      "       [-0.20904842],\n",
      "       [ 0.01759843]]), array([[ 0.51599737],\n",
      "       [-0.14722798],\n",
      "       [ 0.0692641 ]]), array([[-0.21550322],\n",
      "       [-0.83552028],\n",
      "       [-2.97212708]]), array([[-0.22584747],\n",
      "       [-0.82121307],\n",
      "       [-2.98892061]]), array([[-0.22791251],\n",
      "       [-0.81032352],\n",
      "       [-2.9831623 ]]), array([[-0.21393876],\n",
      "       [-0.81065599],\n",
      "       [-3.00513035]]), array([[-0.08404687],\n",
      "       [-0.50754009],\n",
      "       [-3.07768654]]), array([[0.14400152],\n",
      "       [0.36965487],\n",
      "       [3.0205435 ]]), array([[0.18443861],\n",
      "       [0.19209893],\n",
      "       [2.99299408]]), array([[ 0.1669101 ],\n",
      "       [-0.06732032],\n",
      "       [ 3.0398434 ]]), array([[ 0.18863547],\n",
      "       [-0.24056989],\n",
      "       [ 3.08250678]]), array([[ 0.14552781],\n",
      "       [-0.26388679],\n",
      "       [ 3.00445164]]), array([[ 0.12390109],\n",
      "       [-0.28330947],\n",
      "       [ 3.01122819]]), array([[ 0.13407341],\n",
      "       [-0.31187902],\n",
      "       [ 3.02720591]]), array([[ 0.10763437],\n",
      "       [-0.29710282],\n",
      "       [ 3.02582659]]), array([[ 0.08323234],\n",
      "       [-0.24800518],\n",
      "       [ 3.03591959]]), array([[ 0.03431999],\n",
      "       [-0.12990259],\n",
      "       [ 3.06137116]]), array([[-0.28160231],\n",
      "       [ 0.00768099],\n",
      "       [ 3.07794589]]), array([[-0.40780415],\n",
      "       [ 0.02516442],\n",
      "       [ 3.06947008]]), array([[-4.53857257e-01],\n",
      "       [ 1.57883503e-03],\n",
      "       [ 3.10588533e+00]]), array([[-4.44172352e-01],\n",
      "       [ 2.75626119e-03],\n",
      "       [ 3.10922397e+00]]), array([[ 0.42023583],\n",
      "       [-0.0250799 ],\n",
      "       [-3.10305117]]), array([[ 0.38981398],\n",
      "       [-0.01099025],\n",
      "       [-3.11505521]]), array([[ 1.69822883e-01],\n",
      "       [ 2.80746898e-03],\n",
      "       [-3.13152562e+00]]), array([[-0.17405532],\n",
      "       [ 0.07354611],\n",
      "       [ 3.12445571]]), array([[-0.06903332],\n",
      "       [ 0.06314744],\n",
      "       [ 3.11497119]]), array([[0.02640859],\n",
      "       [0.21778695],\n",
      "       [3.11147464]]), array([[0.01737767],\n",
      "       [0.4325429 ],\n",
      "       [3.09597346]]), array([[-0.04751714],\n",
      "       [-0.3295373 ],\n",
      "       [-3.11887973]]), array([[0.06639505],\n",
      "       [0.32919604],\n",
      "       [3.12146631]]), array([[-0.08302883],\n",
      "       [-0.33954234],\n",
      "       [-3.12240862]]), array([[ 0.54761123],\n",
      "       [-0.02360242],\n",
      "       [ 3.02055282]]), array([[ 0.56178723],\n",
      "       [-0.02383973],\n",
      "       [ 3.02912205]]), array([[ 0.57660091],\n",
      "       [-0.01964882],\n",
      "       [ 3.00819828]]), array([[ 0.57852589],\n",
      "       [-0.01219625],\n",
      "       [ 3.02103681]]), array([[ 0.6655206 ],\n",
      "       [-0.02223768],\n",
      "       [ 2.98250066]]), array([[ 0.69723738],\n",
      "       [-0.01420902],\n",
      "       [ 2.97948744]]), array([[ 0.69177257],\n",
      "       [-0.00837355],\n",
      "       [ 2.97353881]]), array([[ 6.84524859e-01],\n",
      "       [-1.41735074e-03],\n",
      "       [ 2.97713630e+00]]), array([[ 0.67232421],\n",
      "       [-0.0063837 ],\n",
      "       [ 2.98804747]]), array([[ 0.66248787],\n",
      "       [-0.00725345],\n",
      "       [ 2.9867839 ]]), array([[ 0.64034912],\n",
      "       [-0.00640832],\n",
      "       [ 2.99489411]]), array([[ 0.63269058],\n",
      "       [-0.00859997],\n",
      "       [ 3.00204634]]), array([[ 0.62584424],\n",
      "       [-0.00900927],\n",
      "       [ 3.00880653]]), array([[ 0.08682219],\n",
      "       [-0.39510417],\n",
      "       [ 2.97119988]]), array([[ 0.08730757],\n",
      "       [-0.37948325],\n",
      "       [ 2.99920101]]), array([[ 0.1059993 ],\n",
      "       [-0.37212186],\n",
      "       [ 2.96075428]]), array([[ 0.10012767],\n",
      "       [-0.34834293],\n",
      "       [ 2.96113384]]), array([[ 0.11111623],\n",
      "       [-0.3402133 ],\n",
      "       [ 2.96330956]]), array([[ 0.12102347],\n",
      "       [-0.34369543],\n",
      "       [ 2.95903598]]), array([[ 0.12985996],\n",
      "       [-0.34289256],\n",
      "       [ 2.95841574]]), array([[ 0.13144803],\n",
      "       [-0.33768734],\n",
      "       [ 2.95044227]]), array([[-0.14894594],\n",
      "       [-0.58015277],\n",
      "       [-3.03954044]]), array([[-0.13358044],\n",
      "       [-0.57746436],\n",
      "       [-3.02371177]]), array([[-0.13177814],\n",
      "       [-0.57220511],\n",
      "       [-3.02247462]]), array([[-0.14187785],\n",
      "       [-0.57545644],\n",
      "       [-3.02512771]]), array([[-0.14252706],\n",
      "       [-0.57156713],\n",
      "       [-3.02584259]]), array([[-0.15033088],\n",
      "       [-0.56776422],\n",
      "       [-3.02385546]]), array([[-0.15854035],\n",
      "       [-0.5607036 ],\n",
      "       [-3.02393835]]), array([[-0.1668998 ],\n",
      "       [-0.55324314],\n",
      "       [-3.03266714]]), array([[-0.12639693],\n",
      "       [-0.50675376],\n",
      "       [-3.04464769]]), array([[-0.27821981],\n",
      "       [-0.01765152],\n",
      "       [ 3.0800358 ]]), array([[-0.35635545],\n",
      "       [ 0.07134931],\n",
      "       [ 3.08008974]]), array([[-0.30615209],\n",
      "       [-0.01328144],\n",
      "       [ 3.0482958 ]]), array([[-0.2974279 ],\n",
      "       [-0.00311004],\n",
      "       [ 3.06024617]]), array([[-0.30255254],\n",
      "       [-0.0074996 ],\n",
      "       [ 3.06281792]]), array([[-0.30629884],\n",
      "       [-0.008965  ],\n",
      "       [ 3.06241547]]), array([[-0.29223917],\n",
      "       [-0.01799883],\n",
      "       [ 3.05827144]]), array([[-0.26928322],\n",
      "       [-0.01900934],\n",
      "       [ 3.05702524]]))\n",
      "tvecs(extrinsic parameter) : \n",
      "\n",
      "(array([[-1.92126302],\n",
      "       [-3.82282975],\n",
      "       [14.26716315]]), array([[-2.98645285],\n",
      "       [-4.33656808],\n",
      "       [13.24585001]]), array([[-1.32426745],\n",
      "       [-3.46203447],\n",
      "       [11.45576144]]), array([[-2.1074267 ],\n",
      "       [-3.65157376],\n",
      "       [11.35260918]]), array([[-2.36065376],\n",
      "       [-3.08889221],\n",
      "       [11.47659999]]), array([[-2.86083224],\n",
      "       [-2.57285056],\n",
      "       [11.02405675]]), array([[-1.81833814],\n",
      "       [-1.58868836],\n",
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      "       [ 2.22599132],\n",
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      "       [ 2.29321178],\n",
      "       [10.15970442]]), array([[ 2.0643309],\n",
      "       [ 2.2345922],\n",
      "       [10.1888677]]), array([[ 1.97555265],\n",
      "       [ 2.53674848],\n",
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      "       [ 1.63111945],\n",
      "       [11.29383694]]), array([[ 2.88330973],\n",
      "       [ 3.92277146],\n",
      "       [12.48118886]]), array([[ 3.2782261 ],\n",
      "       [ 3.93805706],\n",
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      "       [ 2.79646455],\n",
      "       [14.76184375]]), array([[ 2.4511913 ],\n",
      "       [ 2.10410529],\n",
      "       [14.83284042]]), array([[ 2.66336072],\n",
      "       [ 3.69480187],\n",
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      "       [ 4.322558  ],\n",
      "       [12.8201269 ]]), array([[ 2.43586865],\n",
      "       [ 4.22674763],\n",
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      "       [ 3.53099969],\n",
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      "       [ 3.99328205],\n",
      "       [12.68084865]]), array([[ 3.27606869],\n",
      "       [ 4.12123162],\n",
      "       [12.76853145]]), array([[ 3.32441415],\n",
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      "       [ 4.14062358],\n",
      "       [12.79198551]]), array([[ 4.66781959],\n",
      "       [ 3.58845674],\n",
      "       [12.30779048]]), array([[ 3.44712997],\n",
      "       [ 3.29071603],\n",
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      "       [ 3.32975357],\n",
      "       [11.2647451 ]]), array([[2.52114227],\n",
      "       [3.30607769],\n",
      "       [9.10124014]]), array([[1.89512579],\n",
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      "       [ 3.8277506 ],\n",
      "       [12.45240032]]), array([[ 3.50973095],\n",
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      "       [11.85568285]]), array([[2.44285835],\n",
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      "       [9.68652017]]), array([[2.49515364],\n",
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      "       [3.43683619],\n",
      "       [9.87974849]]), array([[ 3.13885401],\n",
      "       [ 2.86235279],\n",
      "       [12.85528128]]), array([[ 3.06833395],\n",
      "       [ 4.15160999],\n",
      "       [12.55440698]]), array([[ 3.72444548],\n",
      "       [ 3.87911485],\n",
      "       [12.95915798]]), array([[ 3.75683145],\n",
      "       [ 3.96240998],\n",
      "       [12.84278717]]), array([[ 3.70238098],\n",
      "       [ 4.0160662 ],\n",
      "       [12.87844692]]), array([[ 3.69819512],\n",
      "       [ 4.02423254],\n",
      "       [12.87634743]]), array([[ 3.8497845 ],\n",
      "       [ 3.9578087 ],\n",
      "       [12.90659758]]), array([[ 3.96707512],\n",
      "       [ 3.93160177],\n",
      "       [12.85005427]]))\n"
     ]
    }
   ],
   "source": [
    "# Extracting path of individual image stored in a given directory\n",
    "images = glob.glob('./image/*.jpg')\n",
    "for fname in images:\n",
    "    img = cv2.imread(fname)\n",
    "    # 轉換成灰階\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",
    "    ret, corners = cv2.findChessboardCorners(gray, CHECKERBOARD, cv2.CALIB_CB_ADAPTIVE_THRESH + cv2.CALIB_CB_FAST_CHECK + cv2.CALIB_CB_NORMALIZE_IMAGE)\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",
    "        objpoints.append(objp)\n",
    "        # refining pixel coordinates for given 2d points.\n",
    "        ## 在原角點的基礎上尋找亞像素角點\n",
    "        # cornerSubPix(image,corners,winSize zeroZone)\n",
    "        '''\n",
    "        winSize = 區域大小為 NXN; N=(winSize*2+1) (計算亞畫素角點時考慮的區域的大小)\n",
    "        zeroZone =  類似於winSize，但是總具有較小的範圍，Size(-1,-1)表示忽略\n",
    "        '''\n",
    "        corners2 = cv2.cornerSubPix(gray, corners, (9,9),(-1,-1), criteria)\n",
    "        imgpoints.append(corners2)\n",
    "\n",
    "        # Draw and display the corners\n",
    "        img = cv2.drawChessboardCorners(img, CHECKERBOARD, corners2, ret)\n",
    "    cv2.namedWindow('img', cv2.WINDOW_NORMAL)\n",
    "    cv2.imshow('img',img)\n",
    "    cv2.waitKey(1500)\n",
    "\n",
    "cv2.destroyAllWindows()\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(intrinsic parameter) : \\n\")\n",
    "print(mtx)\n",
    "print(\"dist : \\n\")\n",
    "print(dist)\n",
    "print(\"rvecs(extrinsic parameter) : \\n\")\n",
    "print(rvecs)\n",
    "print(\"tvecs(extrinsic parameter) : \\n\")\n",
    "print(tvecs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Camera matrix(intrinsic parameter) : \n",
      "\n",
      "[[3.03209507e+03 0.00000000e+00 1.53957273e+03]\n",
      " [0.00000000e+00 3.02940044e+03 2.01690607e+03]\n",
      " [0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n"
     ]
    }
   ],
   "source": [
    "print(\"Camera matrix(intrinsic parameter) : \\n\")\n",
    "print(mtx)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "rvecs(extrinsic parameter - rotation) : \n",
      "\n",
      "(array([[ 0.03874374],\n",
      "       [-0.1436753 ],\n",
      "       [-0.09578558]]), array([[ 0.12259614],\n",
      "       [-0.20454763],\n",
      "       [-0.07648667]]), array([[ 0.20925306],\n",
      "       [-0.17351986],\n",
      "       [-0.0773406 ]]), array([[ 0.3483956 ],\n",
      "       [-0.19293506],\n",
      "       [-0.02102626]]), array([[ 0.37138768],\n",
      "       [-0.1931297 ],\n",
      "       [ 0.03787842]]), array([[ 0.46242887],\n",
      "       [-0.20958239],\n",
      "       [ 0.01747835]]), array([[ 0.51611731],\n",
      "       [-0.1471601 ],\n",
      "       [ 0.06928937]]), array([[-0.21552364],\n",
      "       [-0.83509319],\n",
      "       [-2.97228608]]), array([[-0.22583425],\n",
      "       [-0.82081788],\n",
      "       [-2.98905375]]), array([[-0.22783535],\n",
      "       [-0.80992324],\n",
      "       [-2.98328722]]), array([[-0.21328112],\n",
      "       [-0.8103009 ],\n",
      "       [-3.00533065]]), array([[-0.08425705],\n",
      "       [-0.50705175],\n",
      "       [-3.07779071]]), array([[0.14403834],\n",
      "       [0.36929905],\n",
      "       [3.02059991]]), array([[0.18459827],\n",
      "       [0.19092788],\n",
      "       [2.99316048]]), array([[ 0.16619598],\n",
      "       [-0.06679503],\n",
      "       [ 3.03982064]]), array([[ 0.187007  ],\n",
      "       [-0.24051087],\n",
      "       [ 3.08244659]]), array([[ 0.14679643],\n",
      "       [-0.26368115],\n",
      "       [ 3.00438491]]), array([[ 0.12345814],\n",
      "       [-0.28369602],\n",
      "       [ 3.01127316]]), array([[ 0.13406575],\n",
      "       [-0.31202403],\n",
      "       [ 3.02721982]]), array([[ 0.10753506],\n",
      "       [-0.29711486],\n",
      "       [ 3.0258371 ]]), array([[ 0.08357819],\n",
      "       [-0.24758371],\n",
      "       [ 3.03580812]]), array([[ 0.03843392],\n",
      "       [-0.12786005],\n",
      "       [ 3.06186051]]), array([[-0.28127366],\n",
      "       [ 0.00756114],\n",
      "       [ 3.07797134]]), array([[-0.40735056],\n",
      "       [ 0.02479984],\n",
      "       [ 3.06947776]]), array([[-4.53797716e-01],\n",
      "       [ 1.39001206e-03],\n",
      "       [ 3.10586572e+00]]), array([[-4.44009370e-01],\n",
      "       [ 2.58827949e-03],\n",
      "       [ 3.10922395e+00]]), array([[ 0.42020294],\n",
      "       [-0.02476381],\n",
      "       [-3.1030986 ]]), array([[ 0.38951971],\n",
      "       [-0.0108232 ],\n",
      "       [-3.11511002]]), array([[ 0.16907674],\n",
      "       [ 0.00375517],\n",
      "       [-3.1318559 ]]), array([[-0.17410959],\n",
      "       [ 0.0731973 ],\n",
      "       [ 3.1244248 ]]), array([[-0.07014681],\n",
      "       [ 0.06288928],\n",
      "       [ 3.11485874]]), array([[0.02661804],\n",
      "       [0.21751117],\n",
      "       [3.1115095 ]]), array([[0.01635362],\n",
      "       [0.43152787],\n",
      "       [3.0960038 ]]), array([[-0.04772992],\n",
      "       [-0.32913847],\n",
      "       [-3.1189329 ]]), array([[0.06657881],\n",
      "       [0.32877818],\n",
      "       [3.12149996]]), array([[-0.08318203],\n",
      "       [-0.33905089],\n",
      "       [-3.1224734 ]]), array([[ 0.54763383],\n",
      "       [-0.02379918],\n",
      "       [ 3.0205857 ]]), array([[ 0.56174165],\n",
      "       [-0.02401597],\n",
      "       [ 3.02916419]]), array([[ 0.5765915 ],\n",
      "       [-0.01988409],\n",
      "       [ 3.00822701]]), array([[ 0.57843724],\n",
      "       [-0.01239271],\n",
      "       [ 3.02105511]]), array([[ 0.66559748],\n",
      "       [-0.0223465 ],\n",
      "       [ 2.98252705]]), array([[ 0.69716634],\n",
      "       [-0.01446223],\n",
      "       [ 2.97954115]]), array([[ 0.69167725],\n",
      "       [-0.00862198],\n",
      "       [ 2.97360167]]), array([[ 6.84373886e-01],\n",
      "       [-1.72789383e-03],\n",
      "       [ 2.97718732e+00]]), array([[ 0.67227233],\n",
      "       [-0.00665691],\n",
      "       [ 2.98810051]]), array([[ 0.66235125],\n",
      "       [-0.00737361],\n",
      "       [ 2.98686075]]), array([[ 0.64030068],\n",
      "       [-0.00664431],\n",
      "       [ 2.99494567]]), array([[ 0.63265099],\n",
      "       [-0.00882011],\n",
      "       [ 3.00209849]]), array([[ 0.62585249],\n",
      "       [-0.0092848 ],\n",
      "       [ 3.00886056]]), array([[ 0.08689509],\n",
      "       [-0.39514153],\n",
      "       [ 2.97120966]]), array([[ 0.08718148],\n",
      "       [-0.37936664],\n",
      "       [ 2.99923032]]), array([[ 0.10613572],\n",
      "       [-0.37229673],\n",
      "       [ 2.96073312]]), array([[ 0.10003784],\n",
      "       [-0.3484677 ],\n",
      "       [ 2.96111967]]), array([[ 0.111059  ],\n",
      "       [-0.3404467 ],\n",
      "       [ 2.96328126]]), array([[ 0.12093718],\n",
      "       [-0.34385626],\n",
      "       [ 2.95903895]]), array([[ 0.12978667],\n",
      "       [-0.34310755],\n",
      "       [ 2.95841271]]), array([[ 0.13154769],\n",
      "       [-0.33785454],\n",
      "       [ 2.95044435]]), array([[-0.14889908],\n",
      "       [-0.57995824],\n",
      "       [-3.03961107]]), array([[-0.13360868],\n",
      "       [-0.5770931 ],\n",
      "       [-3.02378555]]), array([[-0.13170723],\n",
      "       [-0.57185687],\n",
      "       [-3.02252949]]), array([[-0.14179617],\n",
      "       [-0.57508817],\n",
      "       [-3.025197  ]]), array([[-0.14254266],\n",
      "       [-0.57122295],\n",
      "       [-3.02590315]]), array([[-0.15027611],\n",
      "       [-0.56736519],\n",
      "       [-3.02393073]]), array([[-0.15856466],\n",
      "       [-0.56034874],\n",
      "       [-3.02401691]]), array([[-0.16695032],\n",
      "       [-0.55284364],\n",
      "       [-3.03273204]]), array([[-0.125661  ],\n",
      "       [-0.50638467],\n",
      "       [-3.04494746]]), array([[-0.27701606],\n",
      "       [-0.01740266],\n",
      "       [ 3.08027225]]), array([[-0.35622601],\n",
      "       [ 0.07097262],\n",
      "       [ 3.080043  ]]), array([[-0.3058415 ],\n",
      "       [-0.01320893],\n",
      "       [ 3.04828648]]), array([[-0.29717599],\n",
      "       [-0.00338531],\n",
      "       [ 3.06025553]]), array([[-0.30244551],\n",
      "       [-0.00761794],\n",
      "       [ 3.062806  ]]), array([[-0.30605922],\n",
      "       [-0.009231  ],\n",
      "       [ 3.06241286]]), array([[-0.29198306],\n",
      "       [-0.01816585],\n",
      "       [ 3.05829017]]), array([[-0.26908592],\n",
      "       [-0.01934026],\n",
      "       [ 3.05703167]]))\n"
     ]
    }
   ],
   "source": [
    "print(\"rvecs(extrinsic parameter - rotation) : \\n\")\n",
    "print(rvecs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tvecs(extrinsic parameter) : \n",
      "\n",
      "(array([[-1.92211326],\n",
      "       [-3.82593529],\n",
      "       [14.26286739]]), array([[-2.98723997],\n",
      "       [-4.33932751],\n",
      "       [13.2419361 ]]), array([[-1.32488614],\n",
      "       [-3.46491686],\n",
      "       [11.44745228]]), array([[-2.10795316],\n",
      "       [-3.64949385],\n",
      "       [11.33966254]]), array([[-2.36125968],\n",
      "       [-3.0911657 ],\n",
      "       [11.47370388]]), array([[-2.8611693 ],\n",
      "       [-2.57417679],\n",
      "       [11.02078557]]), array([[-1.81899192],\n",
      "       [-1.59081133],\n",
      "       [10.24757616]]), array([[ 1.93447403],\n",
      "       [ 2.22377334],\n",
      "       [10.07732881]]), array([[ 2.10268096],\n",
      "       [ 2.29120145],\n",
      "       [10.15736653]]), array([[ 2.06375868],\n",
      "       [ 2.23266564],\n",
      "       [10.18652308]]), array([[ 1.97523159],\n",
      "       [ 2.53590754],\n",
      "       [10.12808656]]), array([[ 1.37210998],\n",
      "       [ 1.62934138],\n",
      "       [11.29091168]]), array([[ 2.88259444],\n",
      "       [ 3.92034954],\n",
      "       [12.47857623]]), array([[ 3.2772662 ],\n",
      "       [ 3.93565122],\n",
      "       [13.79035067]]), array([[ 2.99352833],\n",
      "       [ 2.79302415],\n",
      "       [14.75828543]]), array([[ 2.45133918],\n",
      "       [ 2.10041069],\n",
      "       [14.83218052]]), array([[ 2.66259058],\n",
      "       [ 3.69331634],\n",
      "       [13.47319841]]), array([[ 2.44188116],\n",
      "       [ 4.32024854],\n",
      "       [12.81858805]]), array([[ 2.43512069],\n",
      "       [ 4.22443291],\n",
      "       [12.40172715]]), array([[ 2.40044228],\n",
      "       [ 4.34640028],\n",
      "       [12.00382559]]), array([[ 2.35773537],\n",
      "       [ 4.48895873],\n",
      "       [12.05196216]]), array([[ 3.06746504],\n",
      "       [ 3.97518828],\n",
      "       [12.98035891]]), array([[ 3.98538878],\n",
      "       [ 3.52851053],\n",
      "       [13.03303426]]), array([[ 3.69470337],\n",
      "       [ 3.99073463],\n",
      "       [12.67773444]]), array([[ 3.27556891],\n",
      "       [ 4.11879507],\n",
      "       [12.76565158]]), array([[ 3.32382201],\n",
      "       [ 4.04022028],\n",
      "       [12.74325685]]), array([[ 3.42913539],\n",
      "       [ 4.13168854],\n",
      "       [12.74516945]]), array([[ 3.46783906],\n",
      "       [ 4.13826725],\n",
      "       [12.78848894]]), array([[ 4.66859159],\n",
      "       [ 3.58825917],\n",
      "       [12.30534371]]), array([[ 3.44724811],\n",
      "       [ 3.28871418],\n",
      "       [11.27380906]]), array([[ 3.26571163],\n",
      "       [ 3.32751359],\n",
      "       [11.26452333]]), array([[2.52053303],\n",
      "       [3.30427248],\n",
      "       [9.0990041 ]]), array([[1.89573388],\n",
      "       [4.44398306],\n",
      "       [8.41550606]]), array([[1.59893244],\n",
      "       [3.67183229],\n",
      "       [9.3262416 ]]), array([[1.80312369],\n",
      "       [3.65055302],\n",
      "       [9.48281244]]), array([[1.79453993],\n",
      "       [3.68973314],\n",
      "       [9.50601703]]), array([[ 2.81858799],\n",
      "       [ 3.50392104],\n",
      "       [10.85344325]]), array([[ 2.69778607],\n",
      "       [ 3.4653384 ],\n",
      "       [10.7950571 ]]), array([[ 2.71195167],\n",
      "       [ 3.65067962],\n",
      "       [10.34185169]]), array([[2.37625835],\n",
      "       [3.61807746],\n",
      "       [9.8684792 ]]), array([[3.04082313],\n",
      "       [3.6655271 ],\n",
      "       [9.70984321]]), array([[3.02310981],\n",
      "       [3.68670915],\n",
      "       [9.56733942]]), array([[3.01751738],\n",
      "       [3.77351964],\n",
      "       [9.48642303]]), array([[2.92789015],\n",
      "       [3.79134876],\n",
      "       [9.42499376]]), array([[2.76448004],\n",
      "       [3.76843745],\n",
      "       [9.4422192 ]]), array([[2.73257917],\n",
      "       [3.76152029],\n",
      "       [9.43418712]]), array([[2.53894929],\n",
      "       [3.76715759],\n",
      "       [9.41302602]]), array([[2.40971791],\n",
      "       [3.67798527],\n",
      "       [9.42007475]]), array([[2.31885775],\n",
      "       [3.67115897],\n",
      "       [9.41852076]]), array([[ 2.84318589],\n",
      "       [ 3.69528023],\n",
      "       [12.96879402]]), array([[ 2.88041092],\n",
      "       [ 3.82550914],\n",
      "       [12.4495956 ]]), array([[ 3.50906491],\n",
      "       [ 4.03219494],\n",
      "       [12.2993585 ]]), array([[ 3.53867938],\n",
      "       [ 4.19523703],\n",
      "       [11.98823164]]), array([[ 3.57951771],\n",
      "       [ 4.24483656],\n",
      "       [11.89507323]]), array([[ 3.7479822 ],\n",
      "       [ 4.17816196],\n",
      "       [11.88169909]]), array([[ 3.85231889],\n",
      "       [ 4.1759303 ],\n",
      "       [11.92351944]]), array([[ 3.93880308],\n",
      "       [ 4.18552439],\n",
      "       [11.85262796]]), array([[2.44253354],\n",
      "       [3.79635113],\n",
      "       [9.86864176]]), array([[2.35711004],\n",
      "       [3.58840702],\n",
      "       [9.82807893]]), array([[2.34330299],\n",
      "       [3.61188531],\n",
      "       [9.78657733]]), array([[2.41080616],\n",
      "       [3.62178879],\n",
      "       [9.7149632 ]]), array([[2.42228504],\n",
      "       [3.6213084 ],\n",
      "       [9.7306718 ]]), array([[2.45303801],\n",
      "       [3.57897174],\n",
      "       [9.68464656]]), array([[2.49461403],\n",
      "       [3.53526404],\n",
      "       [9.71036872]]), array([[2.63573258],\n",
      "       [3.53235965],\n",
      "       [9.74072633]]), array([[2.48826593],\n",
      "       [3.43450141],\n",
      "       [9.88013811]]), array([[ 3.13779339],\n",
      "       [ 2.85995211],\n",
      "       [12.84793979]]), array([[ 3.0680889 ],\n",
      "       [ 4.14895664],\n",
      "       [12.55255602]]), array([[ 3.72415437],\n",
      "       [ 3.87654301],\n",
      "       [12.95464088]]), array([[ 3.75621728],\n",
      "       [ 3.95990949],\n",
      "       [12.83947666]]), array([[ 3.70172055],\n",
      "       [ 4.01351348],\n",
      "       [12.87517293]]), array([[ 3.69756818],\n",
      "       [ 4.02171732],\n",
      "       [12.87328861]]), array([[ 3.84917346],\n",
      "       [ 3.95532544],\n",
      "       [12.90322813]]), array([[ 3.9662329 ],\n",
      "       [ 3.92914228],\n",
      "       [12.84686999]]))\n"
     ]
    }
   ],
   "source": [
    "print(\"tvecs(extrinsic parameter) : \\n\")\n",
    "print(tvecs)"
   ]
  }
 ],
 "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": "3.8.8 (default, Apr 13 2021, 15:08:03) [MSC v.1916 64 bit (AMD64)]"
  },
  "orig_nbformat": 4,
  "vscode": {
   "interpreter": {
    "hash": "2469a70536e4d2335a2ea8907942d0699c37342a371ac185bdb5b0aa6f073890"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}