OpenCV detectMarkers()报'cameraMatrix'无效参数错误原因咨询

完整错误信息：

OpenCV(4.7.0) :-1: error: (-5:Bad argument) in function 'detectMarkers'
> Overload resolution failed:
>  - 'cameraMatrix' is an invalid keyword argument for detectMarkers()

用户表示相机标定代码正常，已输入标定参数，但运行时仍出现该错误，代码如下：

import numpy as np
import cv2
import sys
import time


ARUCO_DICT = {
    "DICT_4X4_50": cv2.aruco.DICT_4X4_50,
    "DICT_4X4_100": cv2.aruco.DICT_4X4_100,
    "DICT_4X4_250": cv2.aruco.DICT_4X4_250,
    "DICT_4X4_1000": cv2.aruco.DICT_4X4_1000,
    "DICT_5X5_50": cv2.aruco.DICT_5X5_50,
    "DICT_5X5_100": cv2.aruco.DICT_5X5_100,
    "DICT_5X5_250": cv2.aruco.DICT_5X5_250,
    "DICT_5X5_1000": cv2.aruco.DICT_5X5_1000,
    "DICT_6X6_50": cv2.aruco.DICT_6X6_50,
    "DICT_6X6_100": cv2.aruco.DICT_6X6_100,
    "DICT_6X6_250": cv2.aruco.DICT_6X6_250,
    "DICT_6X6_1000": cv2.aruco.DICT_6X6_1000,
    "DICT_7X7_50": cv2.aruco.DICT_7X7_50,
    "DICT_7X7_100": cv2.aruco.DICT_7X7_100,
    "DICT_7X7_250": cv2.aruco.DICT_7X7_250,
    "DICT_7X7_1000": cv2.aruco.DICT_7X7_1000,
    "DICT_ARUCO_ORIGINAL": cv2.aruco.DICT_ARUCO_ORIGINAL,
    "DICT_APRILTAG_16h5": cv2.aruco.DICT_APRILTAG_16h5,
    "DICT_APRILTAG_25h9": cv2.aruco.DICT_APRILTAG_25h9,
    "DICT_APRILTAG_36h10": cv2.aruco.DICT_APRILTAG_36h10,
    "DICT_APRILTAG_36h11": cv2.aruco.DICT_APRILTAG_36h11
}

def aruco_display(corners, ids, rejected, image):
    
    if len(corners) > 0:
        
        ids = ids.flatten()
        
        for (markerCorner, markerID) in zip(corners, ids):
            
            corners = markerCorner.reshape((4, 2))
            (topLeft, topRight, bottomRight, bottomLeft) = corners
            
            topRight = (int(topRight[0]), int(topRight[1]))
            bottomRight = (int(bottomRight[0]), int(bottomRight[1]))
            bottomLeft = (int(bottomLeft[0]), int(bottomLeft[1]))
            topLeft = (int(topLeft[0]), int(topLeft[1]))

            cv2.line(image, topLeft, topRight, (0, 255, 0), 2)
            cv2.line(image, topRight, bottomRight, (0, 255, 0), 2)
            cv2.line(image, bottomRight, bottomLeft, (0, 255, 0), 2)
            cv2.line(image, bottomLeft, topLeft, (0, 255, 0), 2)
            
            cX = int((topLeft[0] + bottomRight[0]) / 2.0)
            cY = int((topLeft[1] + bottomRight[1]) / 2.0)
            cv2.circle(image, (cX, cY), 4, (0, 0, 255), -1)
            
            cv2.putText(image, str(markerID),(topLeft[0], topLeft[1] - 10), cv2.FONT_HERSHEY_SIMPLEX,
                0.5, (0, 255, 0), 2)
            print("[Inference] ArUco marker ID: {}".format(markerID))
            
    return image


def pose_estimation(frame, aruco_dict_type, matrix_coefficients, distortion_coefficients):

    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    cv2.aruco_dict = cv2.aruco.getPredefinedDictionary(aruco_dict_type)
    parameters = cv2.aruco.DetectorParameters()

    corners, ids, rejected_img_points = cv2.aruco.detectMarkers(gray, cv2.aruco_dict,parameters=parameters,
        cameraMatrix=matrix_coefficients,
        distCoeff=distortion_coefficients)

    if len(corners) > 0:
        for i in range(0, len(ids)):
           
            rvec, tvec, markerPoints = cv2.aruco.estimatePoseSingleMarkers(corners[i], 0.02, matrix_coefficients,
                                                                       distortion_coefficients)
            
            cv2.aruco.drawDetectedMarkers(frame, corners) 

            cv2.aruco.drawAxis(frame, matrix_coefficients, distortion_coefficients, rvec, tvec, 0.01)  

    return frame


aruco_type = "DICT_4X4_50"

arucoDict = cv2.aruco.getPredefinedDictionary(ARUCO_DICT[aruco_type])

arucoParams = cv2.aruco.DetectorParameters()

intrinsic_camera = np.array(((981.69820777, 0, 637.86160616),(0,983.8672381, 364.31555519),(0,0,1)))
distortion = np.array((0.0366562741,-0.153342145,-0.000307462615,-0.000078917106,0.215865749))

cap = cv2.VideoCapture(0)

cap.set(cv2.CAP_PROP_FRAME_WIDTH, 1280)
cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 720)

while cap.isOpened():
    
    ret, img = cap.read()

    output = pose_estimation(img, ARUCO_DICT[aruco_type], intrinsic_camera, distortion)

    cv2.imshow('Estimated Pose', output)

    key = cv2.waitKey(1) & 0xFF
    if key == ord('q'):
        break

cap.release()
cv2.destroyAllWindows()

错误原因及解决方法 #

核心原因 #

cv2.aruco.detectMarkers() 函数不接受cameraMatrix和distCoeff作为关键字参数，这两个参数是用于姿态估计的，而非标记检测。

你混淆了检测与姿态估计的函数职责：

• detectMarkers() 仅负责识别图像中的ArUco标记轮廓，不需要相机内参；
• estimatePoseSingleMarkers() 才需要cameraMatrix和distCoeff来计算标记在3D空间中的位姿。

修正步骤 #

1. 移除detectMarkers()中的相机参数：
   将pose_estimation函数中的detectMarkers调用修改为：

   corners, ids, rejected_img_points = cv2.aruco.detectMarkers(gray, cv2.aruco_dict, parameters=parameters)
   

2. 保留姿态估计的参数：
   当前estimatePoseSingleMarkers()中传入matrix_coefficients和distortion_coefficients的写法是正确的，无需修改。

修正后的pose_estimation函数 #

def pose_estimation(frame, aruco_dict_type, matrix_coefficients, distortion_coefficients):

    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    aruco_dict = cv2.aruco.getPredefinedDictionary(aruco_dict_type)
    parameters = cv2.aruco.DetectorParameters()

    # 仅传递必要参数给detectMarkers
    corners, ids, rejected_img_points = cv2.aruco.detectMarkers(gray, aruco_dict, parameters=parameters)

    if len(corners) > 0:
        for i in range(0, len(ids)):
           
            rvec, tvec, markerPoints = cv2.aruco.estimatePoseSingleMarkers(corners[i], 0.02, matrix_coefficients,
                                                                       distortion_coefficients)
            
            cv2.aruco.drawDetectedMarkers(frame, corners) 

            cv2.aruco.drawAxis(frame, matrix_coefficients, distortion_coefficients, rvec, tvec, 0.01)  

    return frame

（注：建议将cv2.aruco_dict改为局部变量aruco_dict，避免污染全局命名空间）

内容的提问来源于stack exchange，提问作者NiccyT