aruco_decode.py

import cv2

#Define globals

MAX_SIZE = 406

#Define helper functions

def extractAruco(img):

    #Inverse threshold to get the inner contour
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    ret, th = cv2.threshold(gray, 127,255,cv2.THRESH_BINARY_INV)

    #Crop image
    contours, hierarchy = cv2.findContours(th, cv2.RETR_EXTERNAL,
                                           cv2.CHAIN_APPROX_SIMPLE)
    contours = contours[0]

    epsilon = 0.1*cv2.arcLength(contours,True)
    approx = cv2.approxPolyDP(contours,epsilon,True)

    image_crop=gray[approx[0,0,1]:approx[2,0,1],approx[0,0,0]:approx[2,0,0]]
    cv2.imshow("Crop", image_crop)

    #Return extracted image
    return image_crop


def findArucoID(inp_img):

    #Extract image
    im = extractAruco(inp_img)

    #Resize it to smaller size for check
    im = cv2.resize(im, (MAX_SIZE,MAX_SIZE))

    #Remove padding
    width = MAX_SIZE / 7
    im = im[width:width*6,width:width*6]
    cv2.imshow("Padding", im)

    #Calculate ID
    ret_val = 0

    for y in range(5):
        _val1 = int(im[(y * width) +  (width / 2), width + width / 2]) #im[y, x] format
        _val2 = int(im[(y * width) +  (width / 2), 3 * width + width / 2]) #im[y, x] format

        if _val1 == 255:
            _val1 = 1

        if _val2 == 255:
            _val2 = 1


        ret_val = ret_val * 2 + _val1
        ret_val = ret_val * 2 + _val2

    return ret_val



image = cv2.imread("aruco_192.png")
ID = findArucoID(image)
cv2.waitKey(0)
cv2.destroyAllWindows()

print "Marker ID is", ID