Camera Calibration

Generate Calibration Pattern

Install svgfig

git clone https://github.com/jpivarski/svgfig.git
cd svgfig/
python2 setup.py install # cannot use python3

Download gen_pattern.py

# row = 9, col = 6, squares, square_width 20mm
python2 gen_pattern.py -o chessboard.svg --rows 9 --columns 6 --type checkerboard -u mm --square_size 20

# row = 7, col = 5, circles, radius 5 inches
python2 gen_pattern.py -o circleboard.svg --rows 7 --columns 5 --type circles --square_size 5 -u inches

# row = 10, col = 8, square size 10mm and less spacing between circles
python2 gen_pattern.py -o acircleboard.svg --rows 7 --columns 5 --type acircles --square_size 10 --radius_rate 2

Run Calibration Program to Compute Coefficients

import numpy as np
import cv2
import glob

# termination criteria
criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001)

# prepare object points, like (0,0,0), (1,0,0), (2,0,0) ....,(6,5,0)
objp = np.zeros((6*7,3), np.float32)
objp[:,:2] = np.mgrid[0:7,0:6].T.reshape(-1,2)

# Arrays to store object points and image points from all the images.
objpoints = [] # 3d point in real world space
imgpoints = [] # 2d points in image plane.

images = glob.glob('*.jpg')

for fname in images:
  img = cv2.imread(fname)
  gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)

  # Find the chess board corners
  ret, corners = cv2.findChessboardCorners(gray, (7,6),None)

  # If found, add object points, image points (after refining them)
  if ret == True:
      objpoints.append(objp)

      cv2.cornerSubPix(gray,corners,(11,11),(-1,-1),criteria)
      imgpoints.append(corners)

      # Draw and display the corners
      cv2.drawChessboardCorners(img, (7,6), corners2,ret)
      cv2.imshow('img',img)
      cv2.waitKey(500)

cv2.destroyAllWindows()