簡單的玩了下opencv里頭的aruco，用的手機相機，手機裝了個 ip攝像頭，這樣視頻就可以傳到電腦上了。
首先是標定，我沒打印chessboard，直接在電腦屏幕上顯示，拍了17張，大概如下：
又在手機上裝了個 尺子 之類的app，比划着量了下，每個格子大概是18.1 mm，這個棋盤是10 x 7的棋盤。
要pip install opencv-contrib-python才有擴展模塊，擴展模塊中包含aruco
然后標定了一下：
1 import cv2 2 import numpy as np 3 import glob 4 import matplotlib.pyplot as plt 5 import matplotlib.patches as patches 6 7 8 # 找棋盤格角點 9 10 criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001) # 閾值 11 #棋盤格模板規格 12 w = 9 # 10 - 1 13 h = 6 # 7 - 1 14 # 世界坐標系中的棋盤格點,例如(0,0,0), (1,0,0), (2,0,0) ....,(8,5,0)，去掉Z坐標，記為二維矩陣 15 objp = np.zeros((w*h,3), np.float32) 16 objp[:,:2] = np.mgrid[0:w,0:h].T.reshape(-1,2) 17 objp = objp*18.1 # 18.1 mm 18 19 # 儲存棋盤格角點的世界坐標和圖像坐標對 20 objpoints = [] # 在世界坐標系中的三維點 21 imgpoints = [] # 在圖像平面的二維點 22 23 images = glob.glob('./chessboard/*.jpg') # 拍攝的十幾張棋盤圖片所在目錄 24 25 i = 1 26 for fname in images: 27 28 img = cv2.imread(fname) 29 gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY) 30 # 找到棋盤格角點 31 ret, corners = cv2.findChessboardCorners(gray, (w,h),None) 32 # 如果找到足夠點對，將其存儲起來 33 if ret == True: 34 print("i:", i) 35 i = i+1 36 37 cv2.cornerSubPix(gray,corners,(11,11),(-1,-1),criteria) 38 objpoints.append(objp) 39 imgpoints.append(corners) 40 # 將角點在圖像上顯示 41 cv2.drawChessboardCorners(img, (w,h), corners, ret) 42 cv2.namedWindow('findCorners', cv2.WINDOW_NORMAL) 43 cv2.resizeWindow('findCorners', 810, 405) 44 cv2.imshow('findCorners',img) 45 cv2.waitKey(1) 46 cv2.destroyAllWindows() 47 #%% 標定 48 ret, mtx, dist, rvecs, tvecs = \ 49 cv2.calibrateCamera(objpoints, imgpoints, gray.shape[::-1], None, None) 50 51 52 print("ret:",ret ) 53 print("mtx:\n",mtx) # 內參數矩陣 54 print("dist:\n",dist ) # 畸變系數 distortion cofficients = (k_1,k_2,p_1,p_2,k_3) 55 print("rvecs:\n",rvecs) # 旋轉向量 # 外參數 56 print("tvecs:\n",tvecs ) # 平移向量 # 外參數
標定結果里對aruco有用的是 mtx 和 dist。
然后打印包含aruco的marker的紙，運行下面的代碼就可以玩了：
1 import numpy as np 2 import time 3 import cv2 4 import cv2.aruco as aruco 5 6 #with np.load('webcam_calibration_output.npz') as X: 7 # mtx, dist, _, _ = [X[i] for i in ('mtx','dist','rvecs','tvecs')] 8 9 #mtx = 10 #2946.48 0 1980.53 11 #0 2945.41 1129.25 12 #0 0 1 13 14 mtx = np.array([ 15 [2946.48, 0, 1980.53], 16 [ 0, 2945.41, 1129.25], 17 [ 0, 0, 1], 18 ]) 19 #我的手機拍棋盤的時候圖片大小是 4000 x 2250 20 #ip攝像頭拍視頻的時候設置的是 1920 x 1080，長寬比是一樣的， 21 #ip攝像頭設置分辨率的時候注意一下 22 23 24 dist = np.array( [0.226317, -1.21478, 0.00170689, -0.000334551, 1.9892] ) 25 26 video = "http://admin:admin@192.168.1.2:8081/" # 手機ip攝像頭 27 # 根據ip攝像頭在你手機上生成的ip地址更改，右上角可修改圖像分辨率 28 29 cap = cv2.VideoCapture(video) 30 31 32 font = cv2.FONT_HERSHEY_SIMPLEX #font for displaying text (below) 33 34 #num = 0 35 while True: 36 ret, frame = cap.read() 37 # operations on the frame come here 38 39 gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) 40 aruco_dict = aruco.Dictionary_get(aruco.DICT_6X6_250) 41 parameters = aruco.DetectorParameters_create() 42 43 ''' 44 detectMarkers(...) 45 detectMarkers(image, dictionary[, corners[, ids[, parameters[, rejectedI 46 mgPoints]]]]) -> corners, ids, rejectedImgPoints 47 ''' 48 49 #lists of ids and the corners beloning to each id 50 corners, ids, rejectedImgPoints = aruco.detectMarkers(gray, 51 aruco_dict, 52 parameters=parameters) 53 54 # if ids != None: 55 if ids is not None: 56 57 rvec, tvec, _ = aruco.estimatePoseSingleMarkers(corners, 0.05, mtx, dist) 58 # Estimate pose of each marker and return the values rvet and tvec---different 59 # from camera coeficcients 60 (rvec-tvec).any() # get rid of that nasty numpy value array error 61 62 # aruco.drawAxis(frame, mtx, dist, rvec, tvec, 0.1) #Draw Axis 63 # aruco.drawDetectedMarkers(frame, corners) #Draw A square around the markers 64 65 for i in range(rvec.shape[0]): 66 aruco.drawAxis(frame, mtx, dist, rvec[i, :, :], tvec[i, :, :], 0.03) 67 aruco.drawDetectedMarkers(frame, corners) 68 ###### DRAW ID ##### 69 # cv2.putText(frame, "Id: " + str(ids), (0,64), font, 1, (0,255,0),2,cv2.LINE_AA) 70 71 72 else: 73 ##### DRAW "NO IDS" ##### 74 cv2.putText(frame, "No Ids", (0,64), font, 1, (0,255,0),2,cv2.LINE_AA) 75 76 # Display the resulting frame 77 cv2.imshow("frame",frame) 78 79 key = cv2.waitKey(1) 80 81 if key == 27: # 按esc鍵退出 82 print('esc break...') 83 cap.release() 84 cv2.destroyAllWindows() 85 break 86 87 if key == ord(' '): # 按空格鍵保存 88 # num = num + 1 89 # filename = "frames_%s.jpg" % num # 保存一張圖像 90 filename = str(time.time())[:10] + ".jpg" 91 cv2.imwrite(filename, frame)
最后效果如下：
