OpenCV camera calibration and undistort

calib.py

import numpy as np
import cv2
import glob

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

cbrow = 7
cbcol = 9

# prepare object points, like (0,0,0), (1,0,0), (2,0,0) ....,(6,5,0)
objp = np.zeros((cbrow*cbcol,3), np.float32)
objp[:,:2] = np.mgrid[0:cbcol,0:cbrow].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, (cbcol,cbrow),None)

    # If found, add object points, image points (after refining them)
    if ret == True:
        print "%s: success" % fname
        objpoints.append(objp)

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

        # Draw and display the corners
        cv2.drawChessboardCorners(img, (cbcol,cbrow), corners,ret)
        cv2.imshow('img',img)
        cv2.waitKey(150)
    else:
        print "%s: failed" % fname
        cv2.imshow('img',img)
        cv2.waitKey(1)

cv2.destroyAllWindows()

ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera(objpoints, imgpoints, gray.shape[::-1],None,None)

print "mtx"
print mtx
print "dist"
print dist

mean_error = 0
for i in xrange(len(objpoints)):
    imgpoints2, _ = cv2.projectPoints(objpoints[i], rvecs[i], tvecs[i], mtx, dist)
    error = cv2.norm(imgpoints[i],imgpoints2, cv2.NORM_L2)/len(imgpoints2)
    mean_error += error

print "total error: ", mean_error/len(objpoints)

undistort.py

import numpy as np
import cv2
import glob

mtx = np.array([[460.71671753, 0., 288.27396648], [0., 462.18652446, 239.00294897], [0., 0., 1.]])
dist = np.array([-0.35122887, 0.1698431, 0, 0, -0.05083561])

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

for fname in images:
    img = cv2.imread(fname)
    h,w = img.shape[:2]
    newcameramtx, roi = cv2.getOptimalNewCameraMatrix(mtx, dist, (w, h), 0, (w, h))

    dst = cv2.undistort(img, mtx, dist, None, newcameramtx)
    # crop the image
    x,y,w,h = roi
    dst = dst[y:y+h, x:x+w]

    cv2.imshow('undist', dst)
    cv2.waitKey(800)