python实现aruco的生成和检测

OpenCV aruco的生成

import cv2 as cv
import numpy as np

if __name__ == '__main__':


    # Load the predefined dictionary
    dictionary = cv.aruco.Dictionary_get(cv.aruco.DICT_6X6_250)

    # Generate the marker
    imghdr=[]
    for i in range(4):
        markerImage = np.zeros((200, 200), dtype=np.uint8)
        markerImage = cv.aruco.drawMarker(dictionary, i, 200, markerImage, 1);
        imghdr.append(markerImage)

        cv.imwrite(str(i)+".png", markerImage);

有可能出现模块不存在的情况
安装OpenCV contrib包
pip install opencv-contrib-python
如果还是出现包不存在的问题
原因最新的OpenCV好像更改了使用方法
下载4.6.0.66版本实测可用，不必和opencv版本对应

标题 aruco的检测

import imutils
import cv2
import sys

# 构造参数解析器并解析参数


# 定义 OpenCV 支持的每个可能的 ArUco 标签的名称
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}


image = cv2.imread('19.jpg')
image = imutils.resize(image, width=600)
corners=[]
ids=[]
rejected=[]
for key,value in ARUCO_DICT.items():
    arucoDict = cv2.aruco.Dictionary_get(value)
    arucoParams = cv2.aruco.DetectorParameters_create()
    (corners, ids, rejected) = cv2.aruco.detectMarkers(image, arucoDict, parameters=arucoParams)
    if len(corners) > 0:
        break

# 验证至少一个 ArUCo 标记被检测到
if len(corners) > 0:
    # 展平 ArUCo ID 列表
    ids = ids.flatten()
    # 循环检测到的 ArUCo 标记
    for (markerCorner, markerID) in zip(corners, ids):
        # 提取始终按​​以下顺序返回的标记：
        # TOP-LEFT, TOP-RIGHT, BOTTOM-RIGHT, BOTTOM-LEFT
        corners = markerCorner.reshape((4, 2))
        (topLeft, topRight, bottomRight, bottomLeft) = corners
        # 将每个 (x, y) 坐标对转换为整数
        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]))
        # 绘制ArUCo检测的边界框
        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)
        # 计算并绘制 ArUCo 标记的中心 (x, y) 坐标
        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)
        # 在图像上绘制 ArUco 标记 ID
        cv2.putText(image, str(markerID), (topLeft[0], topLeft[1] - 15), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2)
        print("[INFO] ArUco marker ID: {}".format(markerID))
        # 显示输出图像
  cv2.namedWindow("Image1", 0);
  cv2.resizeWindow("Image1", 640, 480);
  cv2.imshow("Image1", image)
  cv2.waitKey(0)
  

检测不成功，字典里可能没有相关字典具体看opencv文档