Hacked python camera calibration in opencv

hack-python-opencv-calibration.py

import numpy as np
import cv2
import glob
import math

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

shape = (7,5)

# prepare object points, like (0,0,0), (1,0,0), (2,0,0) ....,(6,5,0)
objp = np.zeros((shape[0]*shape[1],3), np.float32)
objp[:,:2] = np.mgrid[0:shape[0],0:shape[1]].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('IMG*.jpg')
gray = None

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, shape, None)

	print (fname, ret)

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

		imgpoints.append(corners)
		#corners2 = cv2.cornerSubPix(gray,corners,(11,11),(-1,-1),criteria)
		#imgpoints.append(corners2)

		# Draw and display the corners
		cv2.drawChessboardCorners(img, shape, corners, ret)
		cv2.imwrite('cal'+fname,img)

#cv2.destroyAllWindows()

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

print ("mtx", mtx)
print ("dist", dist)

img = cv2.imread(images[0])
h,  w = img.shape[:2]
print ("(h,  w)", (h,  w))
newcameramtx, roi=cv2.getOptimalNewCameraMatrix(mtx,dist,(w,h),1,(w,h))

print ("newcameramtx", newcameramtx)
print ("roi", roi)

# undistort
dst = cv2.undistort(img, mtx, dist, None, newcameramtx)
cv2.imwrite('calibresult1.png',dst)

# crop the image
x,y,w,h = roi
dst = dst[y:y+h, x:x+w]
cv2.imwrite('calibresult2.png',dst)

#Reprojection error
tot_error = 0.0
tot_error_sq = 0.0
for i in range(len(objpoints)):
    imgpoints2, _ = cv2.projectPoints(objpoints[i], rvecs[i], tvecs[i], mtx, dist)
    error = cv2.norm(imgpoints[i],imgpoints2, cv2.NORM_L2)/len(imgpoints2)
    tot_error += error
    tot_error_sq += error * error

print ("mean absolute error: ", tot_error/len(objpoints))
print ("rms error: ", math.sqrt(tot_error_sq/len(objpoints)))

I believe it should be tot_error += error*error

then print sqrt(tot_error/len(objpoints))

Indeed it's wrong, it should be https://www.fatalerrors.org/a/0d511jg.html - then it matches ret from cv2.calibrateCamera.

I've tried to update the code based on comments and transition to python3.