05_calibrateFisheye_A01677104.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Found 37 valid images for calibration\n",
      "DIM=(1920, 1080)\n",
      "K=np.array([[543.0104867188367, 0.0, 939.0225470258382], [0.0, 542.5485795027022, 537.924099639527], [0.0, 0.0, 1.0]])\n",
      "D=np.array([[-0.03526355863702719], [-0.016844894500392806], [0.008612142278291523], [-0.0022750917496576397]])\n"
     ]
    }
   ],
   "source": [
    "import cv2\n",
    "assert cv2.__version__[0] == '3', 'The fisheye module requires opencv version >= 3.0.0'\n",
    "import numpy as np\n",
    "import os\n",
    "import glob\n",
    "CHECKERBOARD = (6,9)\n",
    "subpix_criteria = (cv2.TERM_CRITERIA_EPS+cv2.TERM_CRITERIA_MAX_ITER, 30, 0.1)\n",
    "calibration_flags = cv2.fisheye.CALIB_RECOMPUTE_EXTRINSIC+cv2.fisheye.CALIB_CHECK_COND+cv2.fisheye.CALIB_FIX_SKEW\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",
    "_img_shape = None\n",
    "objpoints = [] # 3d point in real world space\n",
    "imgpoints = [] # 2d points in image plane.\n",
    "images = glob.glob('/Users/michaelmcquade/Desktop/top/*.jpg')\n",
    "for fname in images:\n",
    "    img = cv2.imread(fname)\n",
    "    if _img_shape == None:\n",
    "        _img_shape = img.shape[:2]\n",
    "    else:\n",
    "        assert _img_shape == img.shape[:2], \"All images must share the same size.\"\n",
    "    gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)\n",
    "    # Find the chess board corners\n",
    "    ret, corners = cv2.findChessboardCorners(gray, CHECKERBOARD, cv2.CALIB_CB_ADAPTIVE_THRESH+cv2.CALIB_CB_FAST_CHECK+cv2.CALIB_CB_NORMALIZE_IMAGE)\n",
    "    # If found, add object points, image points (after refining them)\n",
    "    if ret == True:\n",
    "        objpoints.append(objp)\n",
    "        cv2.cornerSubPix(gray,corners,(3,3),(-1,-1),subpix_criteria)\n",
    "        imgpoints.append(corners)\n",
    "N_OK = len(objpoints)\n",
    "K = np.zeros((3, 3))\n",
    "D = np.zeros((4, 1))\n",
    "rvecs = [np.zeros((1, 1, 3), dtype=np.float64) for i in range(N_OK)]\n",
    "tvecs = [np.zeros((1, 1, 3), dtype=np.float64) for i in range(N_OK)]\n",
    "rms, _, _, _, _ = \\\n",
    "    cv2.fisheye.calibrate(\n",
    "        objpoints,\n",
    "        imgpoints,\n",
    "        gray.shape[::-1],\n",
    "        K,\n",
    "        D,\n",
    "        rvecs,\n",
    "        tvecs,\n",
    "        calibration_flags,\n",
    "        (cv2.TERM_CRITERIA_EPS+cv2.TERM_CRITERIA_MAX_ITER, 30, 1e-6)\n",
    "    )\n",
    "print(\"Found \" + str(N_OK) + \" valid images for calibration\")\n",
    "print(\"DIM=\" + str(_img_shape[::-1]))\n",
    "print(\"K=np.array(\" + str(K.tolist()) + \")\")\n",
    "print(\"D=np.array(\" + str(D.tolist()) + \")\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}