gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
blurred = cv2.GaussianBlur(gray, (5, 5), 0)
cv_show('blurred',blurred)

edged = cv2.Canny(blurred, 75, 200)
cv_show('edged',edged)

# 輪廓檢測
cnts, hierarchy = cv2.findContours(edged.copy(), cv2.RETR_EXTERNAL,
	cv2.CHAIN_APPROX_SIMPLE)
cv2.drawContours(contours_img,cnts,-1,(0,0,255),3) 
cv_show('contours_img',contours_img)
docCnt = None

# 輪廓檢測
cnts, hierarchy = cv2.findContours(edged.copy(), cv2.RETR_EXTERNAL,
	cv2.CHAIN_APPROX_SIMPLE)
cv2.drawContours(contours_img,cnts,-1,(0,0,255),3) 
cv_show('contours_img',contours_img)

def four_point_transform(image, pts):
	# 獲取輸入坐標點
	rect = order_points(pts)
	(tl, tr, br, bl) = rect

	# 計算輸入的w和h值
	widthA = np.sqrt(((br[0] - bl[0]) ** 2) + ((br[1] - bl[1]) ** 2))
	widthB = np.sqrt(((tr[0] - tl[0]) ** 2) + ((tr[1] - tl[1]) ** 2))
	maxWidth = max(int(widthA), int(widthB))

	heightA = np.sqrt(((tr[0] - br[0]) ** 2) + ((tr[1] - br[1]) ** 2))
	heightB = np.sqrt(((tl[0] - bl[0]) ** 2) + ((tl[1] - bl[1]) ** 2))
	maxHeight = max(int(heightA), int(heightB))

	# 變換后對應坐標位置
	dst = np.array([
		[0, 0],
		[maxWidth - 1, 0],
		[maxWidth - 1, maxHeight - 1],
		[0, maxHeight - 1]], dtype = "float32")

	# 計算變換矩陣
	M = cv2.getPerspectiveTransform(rect, dst)
	warped = cv2.warpPerspective(image, M, (maxWidth, maxHeight))

	# 返回變換后結(jié)果
	return warped

# 執(zhí)行透視變換

warped = four_point_transform(gray, docCnt.reshape(4, 2))
cv_show('warped',warped)

# 找到每一個圓圈輪廓
cnts, hierarchy = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL,
	cv2.CHAIN_APPROX_SIMPLE)
cv2.drawContours(thresh_Contours,cnts,-1,(0,0,255),3) 
cv_show('thresh_Contours',thresh_Contours)
questionCnts = []

# 遍歷
for c in cnts:
	# 計算比例和大小
	(x, y, w, h) = cv2.boundingRect(c)
	ar = w / float(h)

	# 根據(jù)實際情況指定標準
	if w >= 20 and h >= 20 and ar >= 0.9 and ar <= 1.1:
		questionCnts.append(c)

# 按照從上到下進行排序
questionCnts = sort_contours(questionCnts,
	method="top-to-bottom")[0]
correct = 0

def sort_contours(cnts, method="left-to-right"):
    reverse = False
    i = 0
    if method == "right-to-left" or method == "bottom-to-top":
        reverse = True
    if method == "top-to-bottom" or method == "bottom-to-top":
        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

# 每排有5個選項
for (q, i) in enumerate(np.arange(0, len(questionCnts), 5)):
	# 排序
	cnts = sort_contours(questionCnts[i:i + 5])[0]     #從左到右排列，保持順序：A B C D E
	bubbled = None

	# 遍歷每一個結(jié)果
	for (j, c) in enumerate(cnts):
		# 使用mask來判斷結(jié)果
		mask = np.zeros(thresh.shape, dtype="uint8")
		cv2.drawContours(mask, [c], -1, 255, -1) #-1表示填充
		cv_show('mask',mask)
		# 通過計算非零點數(shù)量來算是否選擇這個答案
		mask = cv2.bitwise_and(thresh, thresh, mask=mask)
		total = cv2.countNonZero(mask)

		# 通過閾值判斷
		if bubbled is None or total > bubbled[0]:
			bubbled = (total, j)

	# 對比正確答案
	color = (0, 0, 255)
	k = ANSWER_KEY[q]

	# 判斷正確
	if k == bubbled[1]:
		color = (0, 255, 0)
		correct += 1
	# 繪圖
	cv2.drawContours(warped, [cnts[k]], -1, color, 3)

score = (correct / 5.0) * 100
print("[INFO] score: {:.2f}%".format(score))
cv2.putText(warped, "{:.2f}%".format(score), (10, 30),
	cv2.FONT_HERSHEY_SIMPLEX, 0.9, (0, 0, 255), 2)
cv2.imshow("Exam", warped)
cv2.waitKey(0)

Connected to pydev debugger (build 201.6668.115)
[INFO] score: 100.00%

Process finished with exit code 0