cv2.imshow("original", people)
    people1 = people.copy()
    gray = cv2.cvtColor(people, cv2.COLOR_BGR2GRAY)
    blur = cv2.GaussianBlur(gray, (1, 1), 1000)
    flag, thresh = cv2.threshold(blur, 120, 255, cv2.THRESH_BINARY)
    # Find contours
    contours, hierarchy = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
    contours = sorted(contours, key=cv2.contourArea, reverse=True)
    # Select long perimeters only
    perimeters = [cv2.arcLength(contours[i], True) for i in range(len(contours))]
    listindex = [i for i in range(15) if perimeters[i] > perimeters[0] / 2]
    numcards = len(listindex)
    # Show image
    imgcont = people.copy()
    [cv2.drawContours(imgcont, [contours[i]], 0, (255, 255, 255), 5) for i in listindex]
    # cv2.imshow("contur", imgcont)

    mask = np.zeros(people.shape[: 2], np.uint8)
    mask1 = people - imgcont
    r, thresh1 = cv2.threshold(mask1, 128, 255, cv2.THRESH_BINARY)
    # cv2.imshow("mask", thresh1)

    bgdModel = np.zeros((1, 65), np.float64)
    fgdModel = np.zeros((1, 65), np.float64)
    # mask[mask1 == 0] = 0
    # mask[mask1 == 255] = 1
    rect = (460, 10, 1200, 800)
    cv2.grabCut(people, mask, rect, bgdModel, fgdModel, 5, cv2.GC_INIT_WITH_RECT)

    mask2 = np.where((mask == 2) | (mask == 0), 0, 1).astype("uint8")

    people = people * mask2[:, :, np.newaxis]

    cv2.imshow("catting", people)

    fon = people1 - people
    cv2.imshow("catting1", fon)
    dst1 = cv2.cvtColor(people, cv2.COLOR_BGR2GRAY)
    r, g, b = cv2.split(people)
    dst = cv2.inpaint(fon, r, 3, cv2.INPAINT_TELEA)
    cv2.imshow("paint", dst)
    cv2.waitKey(0)
    cv2.destroyAllWindows()