镜头的标定与矫正(python)

import cv2
import numpy as np
import glob

criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001)
w,h = 9,6
objp = np.zeros((w * h, 3), np.float32)
objp[:, :2] = np.mgrid[0:w, 0:h].T.reshape(-1, 2)
obj_points = []
img_points = []
images = glob.glob('标定图片地址')
for fname in images:
    img = cv2.imread(fname)
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    size = gray.shape[::-1]
    ret, corners = cv2.findChessboardCorners(gray, (w, h), None)
    if ret == True:
        cv2.cornerSubPix(gray, corners, (11, 11), (-1, -1), criteria)
        obj_points.append(objp)
        img_points.append(corners)
        cv2.drawChessboardCorners(img, (w, h), corners, ret)
        cv2.imwrite('标定图.png', img)

ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera(obj_points, img_points, gray.shape[::-1], None, None)
dist = np.delete(dist, [4])     #有剧烈畸变时删除此行，保留K3

img2 = cv2.imread('待矫正图')
h, w = img2.shape[:2]
newcameramtx, roi = cv2.getOptimalNewCameraMatrix(mtx, dist, (w, h), 1, (w, h))
dst = cv2.undistort(img2, mtx, dist, None, newcameramtx)
cv2.imwrite('矫正图.png', dst)