目的：

實現相機標定，得到相機的內參以及畸變旋轉參數等

嘗試矯正由相機產生的圖像畸變

代碼：

import cv2 as cv import numpy as np import glob import os#循環中斷 criteria=(cv.TERM_CRITERIA_EPS+cv.TERM_CRITERIA_MAX_ITER,30,0.001)#標定板交叉點的個數 row=6 column=4 objp=np.zeros((row*column,3),np.float32) objp[:,:2]=np.mgrid[0:row,0:column].T.reshape(-1,2)objpoints=[] #實際空間3D點 imgpoints=[] #圖像中2D點#批量讀取圖片 images=glob.glob('D:\\python\\photos\\chess\\*.jpg') for fname in images:img=cv.imread(fname)gray=cv.cvtColor(img,cv.COLOR_BGR2GRAY)#找標定板角點ret,corners=cv.findChessboardCorners(gray,(row,column),None)if ret==True:objpoints.append(objp)corners2=cv.cornerSubPix(gray, corners, (11,11), (-1,-1), criteria)imgpoints.append(corners2)#標定相機 ret,Matrix,dist,rvecs,tvecs=cv.calibrateCamera(objpoints,imgpoints,gray.shape[::-1],None,None)datadir="D:\\python\\photos\\chess\\"path=os.path.join(datadir) img_list=os.listdir(path)for i in img_list:img=cv.imread(os.path.join(path,i))h,w=img.shape[:2] newMatrix, roi = cv.getOptimalNewCameraMatrix(Matrix, dist, (w,h), 1, (w,h)) #矯正圖像dst = cv.undistort(img, Matrix, dist, None, newMatrix)cv.imwrite('D:\\python\\practice\\photos\\calibrated\\'+i,dst)#計算重投影誤差 tot_error = 0 for i in range(len(objpoints)):imgpoints2, _ = cv.projectPoints(objpoints[i], rvecs[i], tvecs[i], Matrix, dist)error = cv.norm(imgpoints[i],imgpoints2, cv.NORM_L2)/len(imgpoints2)tot_error += error#輸出參數 print('ret:\n',ret) print('mtx:\n',Matrix) print('dist:\n',dist) print('rvecs:\n',rvecs) print('tvecs:\n',tvecs) print ("total error: ", tot_error/len(objpoints))

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