自学教程：基于python opencv单目相机标定的示例代码

import cv2camera=cv2.VideoCapture(1)i = 0while 1:    (grabbed, img) = camera.read()    cv2.imshow('img',img)    if cv2.waitKey(1) & 0xFF == ord('j'):  # 按j保存一张图片        i += 1        u = str(i)        firename=str('./img'+u+'.jpg')        cv2.imwrite(firename, img)        print('写入：',firename)    if cv2.waitKey(1) & 0xFF == ord('q'):        break

# 相机标定import cv2# 修改目录# 首先读取图像并转为灰度图img = cv2.imread('c1.jpg')gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)# cv2.imshow("img",img)# cv2.imshow("gray",gray)# 使用OpenCV的cv2.findChessboardCorners()函数找出棋盘图中的对角（即图片中黑白相对的点的坐标）,# 同时使用cv2.drawChessboardCorners()将之画出来# cv2.findChessboardCorners参数patternSize取（9,5）－－棋盘图中每行和每列交点的个数# 其原因在于导入的图片./camera_cal/calibration1.jpg数一下交点的数目，一行有９个，一列有５个# Adam博客当中取（9,6）原因在于他的图和我的图不一样，认真数一下可以发现他的图确实是一行９个一列６个角点# 事实证明，可以取任何只要在size小于图片中的交点数即可# 函数解析参见官网https://docs.opencv.org/3.3.0/dc/dbb/tutorial_py_calibration.html# It returns the corner points and retval which will be True if pattern is obtained.# These corners will be placed in an order (from left-to-right, top-to-bottom)ret, corners = cv2.findChessboardCorners(gray, (9, 5),None)print(ret)print(corners)  # 交点坐标if ret == True:    img = cv2.drawChessboardCorners(img, (9, 5), corners, ret)cv2.imshow("final",img)cv2.waitKey()cv2.destroyAllWindows()