带有 ChArUco-Board 的 OpenCV StereoCalibration 提供错误的值

问题描述

我目前正在对两个摄像头进行立体校准。我目前使用的是普通棋盘。我也得到了正确的结果，例如我测量了相机的距离并将它们与平移矩阵进行了比较。

现在我听说如果我使用 ChArUco 板会更健壮。我试图在互联网上找到一些东西，但实际上几乎没有教程。然后我尝试自己编程，但是我得到了无意义的结果。甚至可以使用 ChArUco 板进行立体声校准吗？我已经添加了我的代码的主要部分，也许我做错了什么，有人可以给我一个提示。

谢谢。

import numpy as np
import cv2
import glob
import sys

###################
'''This code is for performing the stereo calibration if 
the intrinsic parameters and the necessary images are available.'''
###################
# Create ChArUco
aruco_dict = cv2.aruco.getPredefinedDictionary(cv2.aruco.DICT_4X4_50)
board = cv2.aruco.CharucoBoard_create(9,6,3,1.25,aruco_dict)
arucoparams = cv2.aruco.DetectorParameters_create()

counter_L,corners_list_L,id_list_L = [],[],[]
counter_R,corners_list_R,id_list_R = [],[]

# load the intrinsic parameters obtained from Int_Calibration.py
with np.load('c2.npz') as X:
    mtxR,distR,rvecsR,tvecsR = [X[i] for i in ('mtx','dist','rvecs','tvecs')]

with np.load('c1.npz') as X:
    mtxL,distL,rvecsl,tvecsl = [X[i] for i in ('mtx','tvecs')]

# Arrays to store object points and image points from all the images.
objpoints = []  # 3d point in real world space
imgpointsL = []  # 2d points in left image plane
imgpointsR = []  # 2d points in right image plane

# Get images for left and right directory
images_l = glob.glob('data1/*.jpg')
images_r = glob.glob('data2/*.jpg')

# Images should be perfect pairs. Otherwise all the calibration will be false
images_l.sort()
images_r.sort()

# Pairs should be same size. Otherwise we have sync problem.
if len(images_l) != len(images_r):
    print("Numbers of left and right images are not equal. They should be pairs.")
    print("Left images count: ",len(images_l))
    print("Right images count: ",len(images_r))
    sys.exit(-1)

# Pair the images for single loop handling
pair_images = zip(images_l,images_r)

for images_l,images_r in pair_images:
    # Left Image Points
    img_l = cv2.imread(images_l)
    grayL = cv2.cvtColor(img_l,cv2.COLOR_BGR2GRAY)
    corners_L,ids_L,rejected_L = cv2.aruco.detectMarkers(grayL,aruco_dict,parameters=arucoparams)
    resp_L,charuco_corners_L,charucos_ids_L = cv2.aruco.interpolateCornersCharuco(corners_L,grayL,board)

    # Right Image Points
    img_r = cv2.imread(images_r)
    grayR = cv2.cvtColor(img_r,cv2.COLOR_BGR2GRAY)
    corners_R,ids_R,rejected_R = cv2.aruco.detectMarkers(grayR,parameters=arucoparams)
    resp_R,charuco_corners_R,charucos_ids_R = cv2.aruco.interpolateCornersCharuco(corners_R,grayR,board)


    objpoints_L,imgpoints_L = cv2.aruco.getBoardobjectAndImagePoints(board,charucos_ids_L)
    objpoints_R,imgpoints_R = cv2.aruco.getBoardobjectAndImagePoints(board,charucos_ids_R)

    if resp_L == resp_R and (resp_L and resp_R) > 1:
        corners_list_L.append(charuco_corners_L)
        corners_list_R.append(charuco_corners_R)

        id_list_L.append(charucos_ids_L)
        id_list_R.append(charucos_ids_R)

        objpoints.append(objpoints_L)
        imgpointsR.append(imgpoints_R)
        imgpointsL.append(imgpoints_L)
        # Draw and display the corners
        cv2.aruco.drawDetectedCornersCharuco(img_l,charucos_ids_L,(255,0))
        cv2.aruco.drawDetectedCornersCharuco(img_r,charucos_ids_R,0))

        cv2.imshow('imgL',img_l)
        cv2.imshow('imgR',img_r)
        cv2.moveWindow("imgR",800,0)
        cv2.waitKey(200)
    else:
        print("Chessboard Couldn't detected. Image pair: ",images_l," and ",images_r)
        continue

cv2.destroyAllWindows()

ret,M1,d1,M2,d2,R,T,E,F = cv2.stereoCalibrate(objpoints,imgpointsL,imgpointsR,mtxL,mtxR,(640,480))
print(T)

解决方法

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