attributeError：模块＆＃x27; cv2.aruco＆＃x27;没有属性＆＃x27; drawframeaxes＆＃x27;

Question

我正在使用VSCODE 1.68.1，Ubuntu 20.04 我正在关注链接（ https> https：// 。

​ Aruco.DrawFrameAxes（DST1，MTX，DIST，RVEC [i，：，：]，tvec [i，：，：，：]，0.03） attributeError：模块'cv2.aruco'没有属性'drawframeaxes'

• 我尝试使用aruco.drawaxis，同样的错误
• 还尝试卸载opencv-python，卸载opencv-contrib-python，然后卸载opencv-contrib-python，然后启用pip3安装opencv-python＆amp＆amp; amp; amp; amp; amp; pip3安装opencv-contrib-python，同样的错误

Answer 1

drawframeaxes是OPENCV中可用的独立模块。它在aruco软件包中找不到。

命令：help（cv2.drawframeaxes）为您提供有关其用法和参数所需的所有详细信息。

在代码中尝试以下内容：

result_img = cv2.drawFrameAxes(dst1, mtx, dist, rvec[i, :, :], tvec[i, :, :],0.03)

Answer 2

您是否尝试过从源来编译OpenCV？我是出于绝望而做到的，此后的功能似乎起作用了。

我也无法使用替代性贡献 - opencv-python软件包。

Answer 3

cv2.drawFrameAxes(frame, matrix_coefficients, distortion_coefficients, rvec, tvec, 0.01) 

我在GitHub页面上将更新的代码上传到Python。
（github -ritabrata -chakraborty/aruco）

Answer 4

"""hello.
this code is runing, 
versions:
Python==3.11.1
opencv-contrib-python==4.9.0.80
opencv-python==4.9.0.80
in this case we have this aruco of 7x7 "DICT_7X7_100" but you can change to "DICT_5X5_100", you must to change in 3 lines of this program"""

生成Aruco图像：
https://chev.me/arucogen/

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.imshow("gray", gray)
    dictionary = cv2.aruco.getPredefinedDictionary(cv2.aruco.DICT_7X7_100) # cv2.aruco.DICT_4X4_250 seleccion del modelo Aruco
    parameters =  cv2.aruco.DetectorParameters()
    detector = cv2.aruco.ArucoDetector(dictionary, parameters)
    corners, ids, rejected_img_points = detector.detectMarkers(gray)
        
    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.drawFrameAxes(frame, matrix_coefficients, distortion_coefficients, rvec, tvec, 0.01)  
    return frame

aruco_type = "DICT_7X7_100"
arucoDict = cv2.aruco.DICT_7X7_100
arucoParams = cv2.aruco.DetectorParameters()

intrinsic_camera = np.array(((933.15867, 0, 657.59),(0,933.1586, 400.36993),(0,0,1)))
distortion = np.array((-0.43948,0.18514,0,0))

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()