import cv2

def do_contours(filename):
    colors = [(0,0,255), (0,255,0), (255,0,0),
              (255,255,0), (255,0,255), (0,255,255),
              (0,0,128), (0,128,0), (128,0,0),
              (128,128,0), (0,128,128), (128,0,128),
              (255,255,255)]
    image = cv2.imread(filename)
    image_gray = cv2.cvtColor(image, cv2.COLOR_RGB2GRAY)
    ret, image_thresh = cv2.threshold(image_gray, 127, 255, 0)
    contours, hierarchy = \
            cv2.findContours(image_thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
    areas = [(i, cv2.contourArea(contours[i])) for i in range(len(contours))]
    areas.sort(key=lambda x: x[1])
    areas.reverse()
    minArea = 50
    result = []
    print(hierarchy)
    for area_entry in areas:
        if area_entry[1] < minArea:
            break
        temp = index = area_entry[0]
        depth = -1
        while temp != -1 and depth < len(colors)-1:
            depth += 1
            temp = hierarchy[0,temp,3]
        contour = contours[index]
        cv2.drawContours(image, [contour], 0, colors[depth], 1)
        result.append(contour)
    cv2.namedWindow(filename)
    cv2.imshow(filename, image)
    return result


res_a = do_contours('star-a.jpg')
print('res_a %d contours' % len(res_a))

res_b = do_contours('star-b.jpg')
print('res_b %d contours' % len(res_b))

res_c = do_contours('star-c.png')
print('res_c %d contours' % len(res_c))

print('match A-B = ', cv2.matchShapes(res_a[0], res_b[0], 1, 0.0))

print('match A-C0 = ', cv2.matchShapes(res_a[0], res_c[0], 1, 0.0))
print('match A-C1 = ', cv2.matchShapes(res_a[0], res_c[1], 1, 0.0))
print('match A-C2 = ', cv2.matchShapes(res_a[0], res_c[2], 1, 0.0))

print('match B-C0 = ', cv2.matchShapes(res_b[0], res_c[0], 1, 0.0))
print('match B-C1 = ', cv2.matchShapes(res_b[0], res_c[1], 1, 0.0))
print('match B-C2 = ', cv2.matchShapes(res_b[0], res_c[2], 1, 0.0))

cv2.waitKey(0)