python计算机视觉标定相机内外参数

import numpy as np import cv2 import glob # 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) objp = np.zeros((6*7,3), np.float32) objp[:,:2] = np.mgrid[0:7,0:6].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('F://Program Files//zengqiang//img//*.jpg') for fname in images: img = cv2.imread(fname) gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY) # Find the chess board corners ret, corners = cv2.findChessboardCorners(gray, (7,6),None) # If found, add object points, image points (after refining them) if ret == True: objpoints.append(objp) corners2 = cv2.cornerSubPix(gray,corners,(11,11),(-1,-1),criteria) imgpoints.append(corners2) # Draw and display the corners img = cv2.drawChessboardCorners(img, (7,6), corners2,ret) cv2.imshow('img',img) cv2.waitKey(300) '''ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera(objpoints, imgpoints, gray.shape[::-1], None, None) print ("ret:", ret) print ("内参数矩阵mtx:\n", mtx) # 内参数矩阵 print ("dist:\n", dist) # 畸变系数 distortion cofficients = (k_1,k_2,p_1,p_2,k_3) print ("rvecs:\n", rvecs) # 旋转向量 # 外参数 print ("tvecs:\n", tvecs) # 平移向量 # 外参数''' #cv2.destroyAllWindows()