# coding:utf-8 import cv2 import numpy as np import glob # 找棋盘格角点 # 阈值 criteria
= (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001) # 棋盘格模板规格

....,(8,5,0)，去掉Z坐标，记为二维矩阵 objp = np.zeros((w * h, 3), np.float32) objp[:, :2] =
np.mgrid[0:w, 0:h].T.reshape(-1, 2) # 储存棋盘格角点的世界坐标和图像坐标对 objpoints = [] #

'jz/*.jpg') for fname in images: img = cv2.imread(fname) gray = cv2.cvtColor(img
, cv2.COLOR_BGR2GRAY) # 找到棋盘格角点 ret, corners = cv2.findChessboardCorners(gray, (
w, h), None) # 将角点在图像上显示 cv2.drawChessboardCorners(img, (w, h), corners, ret)
cv2.imshow('findCorners', img) cv2.waitKey(500) cv2.destroyAllWindows() #

1), criteria) objpoints.append(objp) imgpoints.append(corners) # 标定 ret, mtx,
dist, rvecs, tvecs = cv2.calibrateCamera(objpoints, imgpoints, gray.shape[::-1],
None, None) # 在应用时，将下面两个写死 print(mtx) print(dist) # 去畸变 img2 = cv2.imread(
'77.jpg') h, w = img2.shape[:2] newcameramtx, roi = cv2.
getOptimalNewCameraMatrix(mtx, dist, (w, h), 0, (w, h)) # 自由比例参数 dst = cv2.
undistort(img2, mtx, dist, None, newcameramtx) # 根据前面ROI区域裁剪图片 # x,y,w,h = roi
# dst = dst[y:y+h, x:x+w] cv2.imwrite('1.jpg', dst) cv2.imshow('findCorners',
dst) cv2.waitKey(0) cv2.destroyAllWindows()

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