image = cv2.imread(args['image'])
accumEdged = np.zeros(image.shape[:2], dtype='uint8')
for chan in cv2.split(image):
?? ?chan = cv2.medianBlur(chan, 11)
? ? edged = cv2.Canny(chan, 50, 200)
? ? accumEdged = cv2.bitwise_or(accumEdged, edged)
cv2.imshow('edge map', accumEdged)

cnts = cv2.findContours(accumEdged.copy(), cv2.RETR_EXTERNAL, ?cv2.CHAIN_APPROX_SIMPLE)
cnts = grab_contours(cnts)
cnts = sorted(cnts, key=cv2.contourArea, reverse=True)[:5]
orig = image.copy()
# unsorted
for (i, c) in enumerate(cnts):
? ? orig = draw_contour(orig, c, i)
cv2.imshow('Unsorted', orig)
cv2.imwrite("./Unsorted.jpg", orig)

def grab_contours(cnts):
? ? # if the length the contours tuple returned by cv2.findContours
? ? # is '2' then we are using either OpenCV v2.4, v4-beta, or
? ? # v4-official
? ? if len(cnts) == 2:
? ? ? ? cnts = cnts[0]

? ? # if the length of the contours tuple is '3' then we are using
? ? # either OpenCV v3, v4-pre, or v4-alpha
? ? elif len(cnts) == 3:
? ? ? ? cnts = cnts[1]

? ? return cnts

def sort_contours(cnts, method='left-to-right'):
? ? # initialize the reverse flag and sort index
? ? reverse = False
? ? i = 0
? ? # handle if sort in reverse
? ? if method == 'right-to-left' or method == 'bottom-to-top':
? ? ? ? reverse = True
? ? # handle if sort against y rather than x of the bounding box
? ? if method == 'bottom-to-top' or method == 'top-to-bottom':
? ? ? ? i = 1

? ? boundingBoxes = [cv2.boundingRect(c) for c in cnts]
? ? (cnts, boundingBoxes) = zip(*sorted(zip(cnts, boundingBoxes), key=lambda b: b[1][i], reverse=reverse))
? ? return (cnts, boundingBoxes)

# sorted
(cnts, boundingboxes) = sort_contours(cnts, method=args['method'])
for (i, c) in enumerate(cnts):
? ? image = draw_contour(image, c, i)
cv2.imshow('Sorted', image)
cv2.waitKey(0)