ref.py

#!/usr/bin/env python
# Reference code after https://docs.opencv.org/4.5.2/dc/dbb/tutorial_py_calibration.html
import numpy as np
import cv2 as cv
import sys, glob

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

CORNERS_W = 9
CORNERS_H = 6

# prepare object points, like (0,0,0), (1,0,0), (2,0,0) ....,(6,5,0)
objp = np.zeros((CORNERS_W*CORNERS_H,3), np.float32)
objp[:,:2] = np.mgrid[0:CORNERS_W,0:CORNERS_H].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 = sys.argv[1:]

for fname in images:
    img = cv.imread(fname)
    gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
    # Find the chess board corners
    ret, corners = cv.findChessboardCorners(gray, (CORNERS_W,CORNERS_H), None)
    # If found, add object points, image points (after refining them)
    if ret:
        objpoints.append(objp)
        corners2 = cv.cornerSubPix(gray,corners, (11,11), (-1,-1), criteria)
        imgpoints.append(corners)
        # Draw and display the corners
        cv.drawChessboardCorners(img, (CORNERS_W,CORNERS_H), corners2, ret)
        cv.imshow('img', img)
        cv.waitKey(100)
    else:
        print('No chessboard found in %s' % fname)
        
ret, mtx, dist, rvecs, tvecs = cv.calibrateCamera(objpoints, imgpoints, gray.shape[::-1], None, None)

print(ret, mtx, dist, rvecs, tvecs)

# Undistort one of the images

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

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

# Compute reprojection error

mean_error = 0
for i in range(len(objpoints)):
    imgpoints2, _ = cv.projectPoints(objpoints[i], rvecs[i], tvecs[i], mtx, dist)
    print(i)
    print(imgpoints2)
    print(imgpoints[i])
    doh
    error = cv.norm(imgpoints[i], imgpoints2, cv.NORM_L2)/len(imgpoints2)
    mean_error += error
print( "total error: {}".format(mean_error/len(objpoints)) )

cv.destroyAllWindows()