calibrate_camera.py

import numpy as np
import cv2
import glob
import yaml

# 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)
a = 9
b = 6
objp = np.zeros((b*a,3), np.float32)
objp[:,:2] = np.mgrid[0:a,0:b].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('chessboard*.jpg')
corners_found = False

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

    # Find the chess board corners
    ret, corners = cv2.findChessboardCorners(gray, (a,b),None)
    print('found corners')

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

        corners2 = cv2.cornerSubPix(gray,corners,(11,11),(-1,-1),criteria)
        print('found subs')
        imgpoints.append(corners2)

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

    data = {'camera_matrix': np.asarray(mtx).tolist(), 'dist_coeff': np.asarray(dist).tolist()}

    with open("calibration.yaml", "w") as f:
        yaml.dump(data, f)