opencv实现答题卡识别_opencv答题卡识别

 
"""
识别答题卡
"""
 
import cv2
import numpy as np
 
def showImg(img_name, img):
cv2.imshow(img_name, img)
cv2.waitKey()
cv2.destroyAllWindows()
 
def get_max_rect(sorted_cnts):
for cnt in sorted_cnts:
# 轮廓近似
possible_cnts = []
epsilon = 0.1 * cv2.arcLength(cnt, True)
approx = cv2.approxPolyDP(cnt, epsilon, True)
if len(approx) == 4:
possible_cnts.append(cnt)
possible_cnts = sorted(possible_cnts, key=lambda x: cv2.arcLength(x, True))
return possible_cnts
 
def get_max_bounding_rect(possible_cnts):
# for cnt in possible_cnts:
# x, y, w, h = cv2.boundingRect(cnt)
 
sorted_cnts = sorted(possible_cnts, key=lambda cnt: cv2.boundingRect(cnt)[2]*cv2.boundingRect(cnt)[3], reverse=True)
print(sorted_cnts[0])
 
def show_countour(img, cnt):
img_copy = img.copy()
cv2.drawContours(img_copy, cnt, -1, (0,255, 0), 3)
showImg("img_copy", img_copy)
 
 
# 读取答题卡图片,并显示
answer_sheet_img = cv2.imread("t1.jpg")
print(answer_sheet_img.shape)
showImg("answer_sheet_img", answer_sheet_img)
 
# 高斯滤波，去除噪音
blur = cv2.GaussianBlur(answer_sheet_img,(5,5),0)
showImg("blur", blur)
 
# 图像转灰度值
sheet_gray = cv2.cvtColor(blur, cv2.COLOR_BGR2GRAY)
showImg("sheet_gray", sheet_gray)
 
# 二值化
retval, sheet_threshold = cv2.threshold(sh