Aruco检测

本文主要是介绍Aruco检测，希望对大家解决编程问题提供一定的参考价值，需要的开发者们随着小编来一起学习吧！

来自：https://blog.dgut.top/2020/07/15/python-aruco/

检测ID

import numpy as np
import time
import cv2
import cv2.aruco as aruco
#读取图片
frame=cv2.imread('/home/shs/0.jpg')
#调整图片大小
frame=cv2.resize(frame,None,fx=1,fy=1,interpolation=cv2.INTER_CUBIC)
#灰度话
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
#设置预定义的字典
aruco_dict = aruco.Dictionary_get(aruco.DICT_6X6_250)
#使用默认值初始化检测器参数
parameters =  aruco.DetectorParameters_create()
#使用aruco.detectMarkers()函数可以检测到marker，返回ID和标志板的4个角点坐标
corners, ids, rejectedImgPoints = aruco.detectMarkers(gray,aruco_dict,parameters=parameters)
#画出标志位置
aruco.drawDetectedMarkers(frame, corners,ids)cv2.imshow("frame",frame)
cv2.imwrite("ID.jpg",frame)
cv2.waitKey(0)
cv2.destroyAllWindows()

检测pose

import numpy as np
import time
import cv2
import cv2.aruco as arucodist=np.array(([[-0.58650416 , 0.59103816, -0.00443272 , 0.00357844 ,-0.27203275]]))
newcameramtx=np.array([[189.076828   ,  0.    ,     361.20126638],[  0 ,2.01627296e+04 ,4.52759577e+02],[0, 0, 1]])
mtx=np.array([[398.12724231  , 0.      ,   304.35638757],[  0.       ,  345.38259888, 282.49861858],[  0.,           0.,           1.        ]])frame=cv2.imread('/home/shs/0.jpg')font = cv2.FONT_HERSHEY_SIMPLEX #font for displaying text (below)gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
aruco_dict = aruco.Dictionary_get(aruco.DICT_6X6_250)
parameters =  aruco.DetectorParameters_create()
dst1 = cv2.undistort(frame, mtx, dist, None, newcameramtx)
'''
detectMarkers(...)detectMarkers(image, dictionary[, corners[, ids[, parameters[, rejectedImgPoints]]]]) -> corners, ids, rejectedImgPoints
'''#使用aruco.detectMarkers()函数可以检测到marker，返回ID和标志板的4个角点坐标
corners, ids, rejectedImgPoints = aruco.detectMarkers(gray,aruco_dict,parameters=parameters)#    如果找不打id
if ids is not None:rvec, tvec, _ = aruco.estimatePoseSingleMarkers(corners, 0.05, mtx, dist)# 估计每个标记的姿态并返回值rvet和tvec ---不同# from camera coeficcients(rvec-tvec).any() # get rid of that nasty numpy value array error#        aruco.drawAxis(frame, mtx, dist, rvec, tvec, 0.1) #绘制轴
#        aruco.drawDetectedMarkers(frame, corners) #在标记周围画一个正方形for i in range(rvec.shape[0]):aruco.drawAxis(frame, mtx, dist, rvec[i, :, :], tvec[i, :, :], 0.03)aruco.drawDetectedMarkers(frame, corners)###### DRAW ID #####cv2.putText(frame, "Id: " + str(ids), (0,64), font, 1, (0,255,0),2,cv2.LINE_AA)else:##### DRAW "NO IDS" #####cv2.putText(frame, "No Ids", (0,64), font, 1, (0,255,0),2,cv2.LINE_AA)# 显示结果框架
cv2.imshow("frame",frame)
cv2.imwrite("frame.jpg", frame)
key = cv2.waitKey(1)if key == 27:         # 按esc键退出print('esc break...')cap.release()cv2.destroyAllWindows()if key == ord(' '):   # 按空格键保存
#        num = num + 1
#        filename = "frames_%s.jpg" % num  # 保存一张图像filename = str(time.time())[:10] + ".jpg"cv2.imwrite(filename, frame)

实时检测pose和ID

import numpy as np
import time
import cv2
import cv2.aruco as aruco# mtx = np.array([
#         [2946.48,       0, 1980.53],
#         [      0, 2945.41, 1129.25],
#         [      0,       0,       1],
#         ])
# #我的手机拍棋盘的时候图片大小是 4000 x 2250
# #ip摄像头拍视频的时候设置的是 1920 x 1080，长宽比是一样的，
# #ip摄像头设置分辨率的时候注意一下
#
#
# dist = np.array( [0.226317, -1.21478, 0.00170689, -0.000334551, 1.9892] )#相机纠正参数# dist=np.array(([[-0.51328742,  0.33232725 , 0.01683581 ,-0.00078608, -0.1159959]]))
#
# mtx=np.array([[464.73554153, 0.00000000e+00 ,323.989155],
#  [  0.,         476.72971528 ,210.92028],
#  [  0.,           0.,           1.        ]])
dist=np.array(([[-0.58650416 , 0.59103816, -0.00443272 , 0.00357844 ,-0.27203275]]))
newcameramtx=np.array([[189.076828   ,  0.    ,     361.20126638],[  0 ,2.01627296e+04 ,4.52759577e+02],[0, 0, 1]])
mtx=np.array([[398.12724231  , 0.      ,   304.35638757],[  0.       ,  345.38259888, 282.49861858],[  0.,           0.,           1.        ]])cap = cv2.VideoCapture(0)font = cv2.FONT_HERSHEY_SIMPLEX #font for displaying text (below)#num = 0
while True:ret, frame = cap.read()h1, w1 = frame.shape[:2]# 读取摄像头画面# 纠正畸变newcameramtx, roi = cv2.getOptimalNewCameraMatrix(mtx, dist, (h1, w1), 0, (h1, w1))dst1 = cv2.undistort(frame, mtx, dist, None, newcameramtx)x, y, w1, h1 = roidst1 = dst1[y:y + h1, x:x + w1]frame=dst1gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)aruco_dict = aruco.Dictionary_get(aruco.DICT_6X6_250)parameters =  aruco.DetectorParameters_create()dst1 = cv2.undistort(frame, mtx, dist, None, newcameramtx)'''detectMarkers(...)detectMarkers(image, dictionary[, corners[, ids[, parameters[, rejectedImgPoints]]]]) -> corners, ids, rejectedImgPoints'''#使用aruco.detectMarkers()函数可以检测到marker，返回ID和标志板的4个角点坐标corners, ids, rejectedImgPoints = aruco.detectMarkers(gray,aruco_dict,parameters=parameters)#    如果找不打idif ids is not None:rvec, tvec, _ = aruco.estimatePoseSingleMarkers(corners, 0.05, mtx, dist)# 估计每个标记的姿态并返回值rvet和tvec ---不同# from camera coeficcients(rvec-tvec).any() # get rid of that nasty numpy value array error#        aruco.drawAxis(frame, mtx, dist, rvec, tvec, 0.1) #绘制轴
#        aruco.drawDetectedMarkers(frame, corners) #在标记周围画一个正方形for i in range(rvec.shape[0]):aruco.drawAxis(frame, mtx, dist, rvec[i, :, :], tvec[i, :, :], 0.03)aruco.drawDetectedMarkers(frame, corners)###### DRAW ID #####cv2.putText(frame, "Id: " + str(ids), (0,64), font, 1, (0,255,0),2,cv2.LINE_AA)else:##### DRAW "NO IDS" #####cv2.putText(frame, "No Ids", (0,64), font, 1, (0,255,0),2,cv2.LINE_AA)# 显示结果框架cv2.imshow("frame",frame)key = cv2.waitKey(1)if key == 27:         # 按esc键退出print('esc break...')cap.release()cv2.destroyAllWindows()breakif key == ord(' '):   # 按空格键保存
#        num = num + 1
#        filename = "frames_%s.jpg" % num  # 保存一张图像filename = str(time.time())[:10] + ".jpg"cv2.imwrite(filename, frame)