我正在使用Charuco模式和OpenCV执行摄像机校准任务，这是我第一次处理这种电路板，但插值步骤后的corners_ids会导致整个角落，在我的情况下是70个角落，但id（0，10，20，30，40，50，60）不准确，我不知道确切的故障，但我怀疑我使用cv2.aruco.CharucoBoard.create创建的板（squaresX，squaresY，squareLength，markerLength，dictionary）不精确，因此我需要熟悉它的人来理解我，这些参数特别是指（squareLength，markerLength）。
this the input imageprovided images after interpolation id(0, 10, 20, 30, 40, 50, 60) each surrounded by black circle which positioned in an inaccurate location显示器

def calibrate_charuco(dirpath, image_format, marker_length, square_length):
    '''Apply camera calibration using aruco.
    The dimensions are in cm.
    '''
    criteria = (cv2.TermCriteria_EPS + cv2.TermCriteria_MAX_ITER, 100, .001)
    aruco_dict = aruco.Dictionary_get(aruco.DICT_4X4_1000)
    board = aruco.CharucoBoard.create(11,8,square_length, marker_length, aruco_dict)
    
    counter, corners_list, id_list = [], [], []
    img_dir = pathlib.Path(dirpath)
    first = 0
    i = 0
    # Find the ArUco markers inside each image
    impaths = img_dir.glob(f'*{image_format}')
    for img in impaths:
        image = cv2.imread(str(img))
        img_gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
        corners, ids, rejected = aruco.detectMarkers(img_gray, aruco_dict)
        for corner in corners:
            cv2.cornerSubPix(img_gray, corner, (3, 3), (-1, -1), criteria)
        resp, charuco_corners, charuco_ids = aruco.interpolateCornersCharuco(corners, ids, img_gray, board, minMarkers=0)
        aruco.drawDetectedCornersCharuco(image, charuco_corners, charuco_ids, (255, 125, 125))
        # If a Charuco board was found, let's collect image/corner points
        # Requiring at least 20 squares
        if resp > 20:
            # Add these corners and ids to our calibration arrays
            corners_list.append(charuco_corners)
            id_list.append(charuco_ids)
        
    # Actual calibration
    ret, mtx, dist, rvecs, tvecs = aruco.calibrateCameraCharuco(
        charucoCorners=corners_list, 
        charucoIds=id_list, 
        board=board, 
        imageSize=img_gray.shape, 
        cameraMatrix=None, 
        distCoeffs=None)
    
    return [ret, mtx, dist, rvecs, tvecs]

# Parameters
IMAGES_DIR = 'Cam1'
IMAGES_FORMAT = 'jpg'
# Dimensions in cm
MARKER_LENGTH = 0.8
SQUARE_LENGTH = 1

ret, mtx, dist, rvecs, tvecs = calibrate_charuco(IMAGES_DIR, IMAGES_FORMAT, MARKER_LENGTH, SQUARE_LENGTH)
print(mtx)
original = cv2.imread('Cam1/G0011233.jpg')
dst = cv2.undistort(original, mtx, dist, None, mtx)
cv2.imwrite('undist_charuco.jpg', dst)