Camera-Calibration/camera_calibration.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%HTML\n",
    "<style> code {background-color : pink !important;} </style>"
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   "metadata": {},
   "source": [
    "Camera Calibration with OpenCV\n",
    "===\n",
    "\n",
    "### Run the code in the cell below to extract object points and image points for camera calibration.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import cv2\n",
    "import glob\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib qt\n",
    "\n",
    "# prepare object points, like (0,0,0), (1,0,0), (2,0,0) ....,(6,5,0)\n",
    "objp = np.zeros((6*8,3), np.float32)\n",
    "objp[:,:2] = np.mgrid[0:8, 0:6].T.reshape(-1,2)\n",
    "\n",
    "# Arrays to store object points and image points from all the images.\n",
    "objpoints = [] # 3d points in real world space\n",
    "imgpoints = [] # 2d points in image plane.\n",
    "\n",
    "# Make a list of calibration images\n",
    "images = glob.glob('calibration_wide/GO*.jpg')\n",
    "\n",
    "# Step through the list and search for chessboard corners\n",
    "for idx, fname in enumerate(images):\n",
    "    img = cv2.imread(fname)\n",
    "    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)\n",
    "\n",
    "    # Find the chessboard corners\n",
    "    ret, corners = cv2.findChessboardCorners(gray, (8,6), None)\n",
    "\n",
    "    # If found, add object points, image points\n",
    "    if ret == True:\n",
    "        objpoints.append(objp)\n",
    "        imgpoints.append(corners)\n",
    "\n",
    "        # Draw and display the corners\n",
    "        cv2.drawChessboardCorners(img, (8,6), corners, ret)\n",
    "        #write_name = 'corners_found'+str(idx)+'.jpg'\n",
    "        #cv2.imwrite(write_name, img)\n",
    "        cv2.imshow('img', img)\n",
    "        cv2.waitKey(500)\n",
    "\n",
    "cv2.destroyAllWindows()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### If the above cell ran sucessfully, you should now have `objpoints` and `imgpoints` needed for camera calibration.  Run the cell below to calibrate, calculate distortion coefficients, and test undistortion on an image!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pickle\n",
    "%matplotlib inline\n",
    "\n",
    "# Test undistortion on an image\n",
    "img = cv2.imread('calibration_wide/test_image.jpg')\n",
    "img_size = (img.shape[1], img.shape[0])\n",
    "\n",
    "# Do camera calibration given object points and image points\n",
    "ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera(objpoints, imgpoints, img_size,None,None)\n",
    "\n",
    "\n",
    "dst = cv2.undistort(img, mtx, dist, None, mtx)\n",
    "cv2.imwrite('calibration_wide/test_undist.jpg',dst)\n",
    "\n",
    "# Save the camera calibration result for later use (we won't worry about rvecs / tvecs)\n",
    "dist_pickle = {}\n",
    "dist_pickle[\"mtx\"] = mtx\n",
    "dist_pickle[\"dist\"] = dist\n",
    "pickle.dump( dist_pickle, open( \"calibration_wide/wide_dist_pickle.p\", \"wb\" ) )\n",
    "#dst = cv2.cvtColor(dst, cv2.COLOR_BGR2RGB)\n",
    "# Visualize undistortion\n",
    "f, (ax1, ax2) = plt.subplots(1, 2, figsize=(20,10))\n",
    "ax1.imshow(img)\n",
    "ax1.set_title('Original Image', fontsize=30)\n",
    "ax2.imshow(dst)\n",
    "ax2.set_title('Undistorted Image', fontsize=30)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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