def get_points(image):
    aruco_dict = aruco.Dictionary_get(cv2.aruco.DICT_6X6_50)
    parameters = aruco.DetectorParameters_create()
    corners, ids, rejectedImgPoints = aruco.detectMarkers(
        image, aruco_dict, parameters=parameters)
    marks = dict()
    dist = list()
    for y in range(len(rejectedImgPoints)):
        k = (abs(rejectedImgPoints[y][0][0][0] - rejectedImgPoints[y][0][2][0]) +
             abs(rejectedImgPoints[y][0][0][1] - rejectedImgPoints[y][0][2][1]))
        if k in marks.keys():
            k += 0.5
        marks[k] = y
        dist.append(k)
    dist.sort()
    dist.reverse()
    newrejectedImgPoints = [rejectedImgPoints[marks[i]] for i in dist[:4]]
    for i in range(len(newrejectedImgPoints)):
        numpy.append(newrejectedImgPoints[i][0],
                     [newrejectedImgPoints[i][0][1][0], newrejectedImgPoints[i][0][0][1]])
        numpy.append(newrejectedImgPoints[i][0],
                     [newrejectedImgPoints[i][0][1][1], newrejectedImgPoints[i][0][0][0]])
    x = 0
    y = 0
    for t in range(len(newrejectedImgPoints)):
        for i in newrejectedImgPoints[t][0]:
            x += i[0]
            y += i[1]
    MeanPoint = Point(x / 16, y / 16)
    Points = list()
    for t in range(len(newrejectedImgPoints)):
        y = 10 ** 9
        for i in newrejectedImgPoints[t][0]:
            if abs(i[1] - MeanPoint.y) + abs(i[0] - MeanPoint.x) < y:
                x = i
                y = abs(i[1] - MeanPoint.y) + abs(i[0] - MeanPoint.x)
        Points.append(x)
    file = open(r'C:\DATA_SCIENTIST\ONTI\Kek-scripts\test.txt', 'w')
    file.write(" ".join([str(i) for i in list(itertools.chain.from_iterable(Points))]))