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table_choose.py
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#!/usr/bin/env python
# encoding: utf-8
import os
import cv2 as cv
import numpy as np
import math
import num_out
import mnist_recognize
import chinese_out
import chinese_out_jiguan
import time_out
import csv
##### 初始化CSV文件 #####
csvfile = open("try1010.csv", 'w')
csvwrite = csv.writer(csvfile)
fileHeader = ["登记表编号","性别","民族","体重","血型","籍贯","高中学校名称","高中专业","高中学位","高中起止时间","高中是否毕业","大专学校名称","大专专业","大专学位","大专起止时间","大专是否毕业","本科学校名称","本科专业","本科学位","本科起止时间","本科是否毕业","研究生学校名称","研究生专业","研究生学位","研究生起止时间","研究生是否毕业","学校名称（其它）","专业（其它）","学位（其它）","起止时间（其它）","是否毕业（其它）"]
csvwrite.writerow(fileHeader)
path = 'test_data'
for (path,dirs,files) in os.walk(path):
for filename in files:
#docu_num = '20110158' #测试单张登记表
##### 按文件名读取登记表 #####
(docu_num,extension) = os.path.splitext(filename)
print "filename:", filename
##### 根据文件名年份的不同区分不同类型的登记表 #####
print docu_num[3]
if docu_num[3] == '1':
if len(docu_num) == 9 or (docu_num[5] == '3' and docu_num[6] == '1'):
table_style = 2
else:
table_style = 1
if docu_num[3] == '3':
table_style = 3
if docu_num[3] == '4' or docu_num[3] == '5':
table_style = 4
jiaozheng = 0
image = cv.imread('test_data/' + docu_num + '.jpg')
rows, cols, channels = image.shape
print rows, cols
image_copy = image.copy()
##### 旋转校正Rotation #####
#统计图中长横线的斜率来判断整体需要旋转矫正的角度
gray = cv.cvtColor(image, cv.COLOR_RGB2GRAY)
if table_style == 1 or table_style == 3 or table_style == 2:
edges = cv.Canny(gray, 50, 150, apertureSize=3) # 50,150,3
cv.imwrite('edges_whole.jpg', edges)
lines = cv.HoughLinesP(edges, 1, np.pi / 180, 500, 0, minLineLength=50, maxLineGap=50)#650,50,20
if table_style == 4:
edges_gray = cv.Canny(gray, 50, 150, apertureSize=3) # 50,150,3
edges = edges_gray[400:1000, 0:1000]
cv.imwrite('edges_whole.jpg', edges)
lines = cv.HoughLinesP(edges, 1, np.pi / 180, 200, 0, minLineLength=50, maxLineGap=35)#650,50,20
pi = 3.1415
theta_total = 0
theta_count = 0
for line in lines:
x1, y1, x2, y2 = line[0]
if table_style == 4:
y1 = y1 + 400
y2 = y2 + 400
rho = np.sqrt((x1 - x2)**2 + (y1 - y2)**2)
theta = math.atan(float(y2 - y1)/float(x2 - x1 + 0.001))
print(rho, theta, x1, y1, x2, y2)
if theta < pi/4 and theta > -pi/4:
theta_total = theta_total + theta
theta_count+=1
cv.line(image_copy, (x1, y1), (x2, y2), (0, 0, 255), 2)
#cv.line(edges, (x1, y1), (x2, y2), (0, 0, 0), 2)
theta_average = theta_total/theta_count
print theta_average, theta_average*180/pi
cv.imwrite('line_detect4rotation.jpg', image_copy)
#cv.imwrite('line_detect4rotation.jpg', ~edges)
#affineShrinkTranslationRotation = cv.getRotationMatrix2D((cols/2, rows/2), theta_average*180/pi, 1)
affineShrinkTranslationRotation = cv.getRotationMatrix2D((0, rows), theta_average*180/pi, 1)
ShrinkTranslationRotation = cv.warpAffine(image, affineShrinkTranslationRotation, (cols, rows))
image_copy = cv.warpAffine(image_copy, affineShrinkTranslationRotation, (cols, rows))
cv.imwrite('image_Rotation.jpg',ShrinkTranslationRotation)
##### 平移校正Move #####
#通过对表格左下角直角进行识别，将其顶点统一平移矫正至(78,1581)
#print "rows: ",rows
roi = image_copy[1450:rows, 0:150]#180
gray = cv.cvtColor(roi, cv.COLOR_RGB2GRAY)
edges = cv.Canny(gray, 50, 150, apertureSize=3) # 50,150,3
roi_mean_set = cv.mean(~edges[0:int((rows-1450)/2), 85:150])#通过区域灰度值特征排除文字对直线识别的干扰
roi_mean = roi_mean_set[0]
#cv.imwrite('edges_sample.jpg', edges)
cv.imwrite('edges_sample.jpg', ~edges[0:int((rows-1450)/2), 75:150])
lines = cv.HoughLinesP(edges, 1.0, np.pi / 180, 35, 0, minLineLength=10,maxLineGap=20)#50,10,20
lines_message_set = []
for line in lines:
x1, y1, x2, y2 = line[0]
y1 = y1 + 1450
y2 = y2 + 1450
rho = np.sqrt((x1 - x2)**2 + (y1 - y2)**2)
xielv = (y2 - y1)/(x2 - x1 + 0.001)
theta = math.atan(float(y2 - y1)/float(x2 - x1 + 0.001))
print(rho, theta, x1, y1, x2, y2, xielv)
lines_message = (rho, theta, x1, y1, x2, y2, xielv)
#cv.line(image, (x1, y1), (x2, y2), (0, 0, 255), 2)
lines_message_set.append(lines_message)
#print len(lines_message_set)
#求点到直线的距离
def point2line_distance(x1,y1,x2,y2,pointPx,pointPy):
A = y1 - y2
B = x2 - x1
C = x1*y2 - y1*x2
distance = abs(A*pointPx + B*pointPy + C)/((A*A + B*B)**0.5)
return distance
lines_cluster_set = []
repeat_num_set = []
for j in range(0,len(lines_message_set)):
for i in range(0,len(lines_message_set)):
if not(j in repeat_num_set):
lines_cluster_set.append(lines_message_set[j])
repeat_num_set.append(j)
print point2line_distance(lines_message_set[i][2], lines_message_set[i][3], lines_message_set[i][4], lines_message_set[i][5], (lines_message_set[j][2]+lines_message_set[j][4])/2, (lines_message_set[j][3]+lines_message_set[j][5])/2)
if i!=j and abs(lines_message_set[j][6] - lines_message_set[i][6]) < 0.1 and point2line_distance(lines_message_set[i][2], lines_message_set[i][3], lines_message_set[i][4], lines_message_set[i][5], (lines_message_set[j][2]+lines_message_set[j][4])/2, (lines_message_set[j][3]+lines_message_set[j][5])/2) <= 10:
repeat_num_set.append(i)
print lines_cluster_set
#对直角的横线、竖线进行分析，缺省时根据表格类型进行矫正
Point_heng = []
Point_shu = []
MiddlePoint_heng = (112,1450+(rows-1450)/2)
MiddlePoint_shu = (75,1450+(rows-1450)/4)
distance2point = rows-1450
distance2point2 = rows-1450
for j in range(0,len(lines_cluster_set)):
if abs(lines_cluster_set[j][6]) < 1:
if ((MiddlePoint_heng[0]-(lines_cluster_set[j][2]+lines_cluster_set[j][4])/2)**2 + (MiddlePoint_heng[1]-(lines_cluster_set[j][3]+lines_cluster_set[j][5])/2)**2)**0.5 < distance2point:
distance2point = ((MiddlePoint_heng[0]-(lines_cluster_set[j][2]+lines_cluster_set[j][4])/2)**2 + (MiddlePoint_heng[1]-(lines_cluster_set[j][3]+lines_cluster_set[j][5])/2)**2)**0.5
Point_heng = lines_cluster_set[j]
else:
if ((MiddlePoint_shu[0]-(lines_cluster_set[j][2]+lines_cluster_set[j][4])/2)**2 + (MiddlePoint_shu[1]-(lines_cluster_set[j][3]+lines_cluster_set[j][5])/2)**2)**0.5 < distance2point2:
distance2point2 = ((MiddlePoint_shu[0]-(lines_cluster_set[j][2]+lines_cluster_set[j][4])/2)**2 + (MiddlePoint_shu[1]-(lines_cluster_set[j][3]+lines_cluster_set[j][5])/2)**2)**0.5
Point_shu = lines_cluster_set[j]
need_stronger = 0
something_missing = 0
#缺省矫正
if Point_shu != []:
if Point_heng == []:
cross_x = 78
cross_y = 1616
something_missing = 1
if len(docu_num) == 9:
something_missing = 0
cross_x = 93
cross_y = 1666
if docu_num[3] == '4':
something_missing = 0
cross_x = 78
cross_y = 1655
if docu_num[3] == '4' and docu_num[5] == '6':
cross_x = 78
cross_y = 1665
else:
cross_x = (Point_shu[3]-Point_shu[6]*Point_shu[2]-Point_heng[3]+Point_heng[6]*Point_heng[2])/(Point_heng[6]-Point_shu[6])
cross_y = Point_heng[6]*cross_x + Point_heng[3] - Point_heng[6]*Point_heng[2]
cv.line(image_copy, (Point_heng[2], Point_heng[3]), (Point_heng[4], Point_heng[5]), (0, 0, 255), 2)
cv.line(image_copy, (Point_shu[2], Point_shu[3]), (Point_shu[4], Point_shu[5]), (0, 0, 255), 2)
else:
cross_x = Point_heng[2]
cross_y = Point_heng[3]
need_stronger = 1
if Point_heng != [] and cross_x > Point_heng[2] and len(docu_num) == 9 and docu_num[6] == '0' and docu_num[7] == '9':
cross_x = 50
cross_y = 1586
if Point_heng != [] and cross_x > Point_heng[2] and len(docu_num) == 9 and docu_num[6] == '1' and docu_num[7] == '8':
cross_x = 50
cross_y = 1616
print 'roi_mean:',roi_mean
if len(docu_num) == 9 and docu_num[7] == '8' and roi_mean < 230:
cross_x = 78
cross_y = 1631
if cross_y - 1648 < 3:
if len(docu_num) == 8 and docu_num[5] == '2' and docu_num[6] == '4':
cross_x = 78
cross_y = 1601
if len(docu_num) == 9 and docu_num[6] == '1' and docu_num[7] == '4':
cross_x = 78
cross_y = 1621
if table_style == 3 and cross_y < 1485:
cross_x = 78
cross_y = 1641
print cross_x,cross_y#当下直角顶点位置，标准位置为78,1581
cv.circle(image_copy, (int(cross_x), int(cross_y)), 3,(255,0,0),3)
cv.rectangle(image_copy,(0,1450),(180,rows),(255,0,0),3)
cv.imwrite('line_detect_possible_demo.jpg', image_copy)
rows, cols, channels = ShrinkTranslationRotation.shape
print rows, cols
affineShrinkTranslation = np.array([[1, 0, int(78 - cross_x)], [0, 1, int(1581 - cross_y)]], np.float32)
#affineShrinkTranslation = np.array([[1, 0, int(78 - 78)], [0, 1, int(1581 - 1581)]], np.float32)
shrinkTwoTimesTranslation = cv.warpAffine(ShrinkTranslationRotation, affineShrinkTranslation, (cols, rows))
image_copy = cv.warpAffine(image_copy, affineShrinkTranslation, (cols, rows))
##### 对201100XXX中左下角表格内有额外竖线的表格进行检测Detect_not_shu_line_in_201100XXX #####
if table_style == 2:
shrinkTwoTimesTranslation_copy_copy = shrinkTwoTimesTranslation.copy()
roi = shrinkTwoTimesTranslation[1350:1548, 125:300]#180
cv.rectangle(image_copy,(125,1350),(300,1548),(255,0,0),3)
gray = cv.cvtColor(roi, cv.COLOR_RGB2GRAY)
edges = cv.Canny(gray, 50, 150, apertureSize=3) # 50,150,3
lines = []
lines = cv.HoughLinesP(edges, 1.0, np.pi / 180, 100, 0, minLineLength=60,maxLineGap=20)#50,10,20
print lines
go_through = 0
try:
if lines == None:
go_through = 0
except:
go_through = 1
if go_through == 1:
pi = 3.1415
theta_total = 0
theta_count = 0
for line in lines:
x1, y1, x2, y2 = line[0]
x1 = x1 + 125
x2 = x2 + 125
y1 = y1 + 1350
y2 = y2 + 1350
rho = np.sqrt((x1 - x2)**2 + (y1 - y2)**2)
theta = math.atan(float(y2 - y1)/float(x2 - x1 + 0.001))
print(rho, theta, x1, y1, x2, y2)
if theta > pi/3 or theta < -pi/3:
table_style = 1
if len(docu_num) == 9 and docu_num[6] == '1' and docu_num[7] == '1':
jiaozheng = 1
cv.line(shrinkTwoTimesTranslation_copy_copy, (x1, y1), (x2, y2), (255, 0, 0), 2)
cv.imwrite('shrinkTwoTimesTranslation_copy_copy.jpg', shrinkTwoTimesTranslation_copy_copy)
##### 提取表格Table_Out #####
#分别通过对二值化后的表格用长横条、长竖条内核进行开操作，将表格分别化为全横线与全竖线，叠加后提取交点，即可得到表格中每个矩形的四个顶点
shrinkTwoTimesTranslation_gray = cv.cvtColor(shrinkTwoTimesTranslation, cv.COLOR_RGB2GRAY)
th2 = cv.adaptiveThreshold(~shrinkTwoTimesTranslation_gray,255,cv.ADAPTIVE_THRESH_MEAN_C,cv.THRESH_BINARY,15,-2)
cv.imwrite('th2.jpg', th2)
#长横条内核处理
shrinkTwoTimesTranslation_copy = shrinkTwoTimesTranslation.copy()
th2_copy = th2.copy()
scale = 44;#20,50,45,40,44
rows,cols = shrinkTwoTimesTranslation_gray.shape
horizontalsize = cols / scale
horizontalStructure = cv.getStructuringElement(cv.MORPH_RECT, (horizontalsize, 1))
erosion = cv.erode(th2,horizontalStructure,iterations = 1)
dilation = cv.dilate(erosion,horizontalStructure,iterations = 1)
#长竖条内核处理
scale = 39;#20,50,45,40,39
horizontalsize2 = rows / scale
horizontalStructure2 = cv.getStructuringElement(cv.MORPH_RECT, (1,horizontalsize2))
erosion2 = cv.erode(th2_copy,horizontalStructure2,iterations = 1)
dilation2 = cv.dilate(erosion2,horizontalStructure2,iterations = 1)
#全横线图与全竖线图叠加，并提取交点
mask = dilation + dilation2
cv.imwrite('mask.jpg', mask)
joints = cv.bitwise_and(dilation, dilation2)
cv.imwrite('joints.jpg', joints)
#根据矩形大小筛选矩形框，并画在矫正后的表格上
#cv.RETR_LIST,cv.CHAIN_APPROX_SIMPLE
mask, contours, hierarchy = cv.findContours(mask,cv.RETR_LIST,cv.CHAIN_APPROX_SIMPLE)
length = len(contours)
print length
small_rects = []
big_rects = []
for i in range(length):
cnt = contours[i]
area = cv.contourArea(cnt)
if area < 10:
continue
approx = cv.approxPolyDP(cnt, 3, True)#3
x, y, w, h = cv.boundingRect(approx)
rect = (x, y, w, h)
#cv.rectangle(img, (x, y), (x+w, y+h), (0, 0, 255), 3)
roi = joints[y:y+h, x:x+w]
roi, joints_contours, joints_hierarchy = cv.findContours(roi,cv.RETR_LIST,cv.CHAIN_APPROX_SIMPLE)
#print len(joints_contours)
#if h < 80 and h > 20 and w > 10 and len(joints_contours)<=4:
if h < 80 and h > 20 and w > 10 and len(joints_contours)<=6:#important
cv.rectangle(image_copy, (x, y), (x+w, y+h), (255-h*3, h*3, 0), 3)
small_rects.append(rect)
cv.imwrite('table_out.jpg', image_copy)
##### 在不同类型的表格中根据信息所在的大致位置获取相应矩形框的坐标 #####
#矫正后的表格中信息的大致位置各在一定范围内，根据大致位置的坐标点筛选出该表中该信息对应的矩形框具体坐标
request_info_set = []#存储筛选出的所需矩形框坐标
#pure_for_message = shrinkTwoTimesTranslation.copy()
print "table_style:", table_style
if table_style == 1:
request_info = (770, 150, 1150-770, 300-150)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(770,150),(1150,300),(255,0,0),1)#登记表编号0
for j in range(0,len(small_rects)):
(x, y, w, h) = small_rects[j]
if x < 1060 and y < 1130 and x+w > 1060 and y+h > 1130 and something_missing == 1:#特殊情况下表格矩形的提取
x_rem = x
y_rem = y
w_rem = w
h_rem = h
for j in range(0,len(small_rects)):
(x, y, w, h) = small_rects[j]
if x < 700 and y < 370 and x+w > 700 and y+h > 370 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#性别1
if x < 880 and y < 370 and x+w > 880 and y+h > 370 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#民族2
if x < 685 and y < 412 and x+w > 685 and y+h > 412 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#体重3
if x < 880 and y < 412 and x+w > 880 and y+h > 412 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(0,0,255),1)#血型4
if x < 890 and y < 452 and x+w > 890 and y+h > 452 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#籍贯5
if x < 486 and y < 1090 and x+w > 486 and y+h > 1090 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#高中学校名称6
if x < 696 and y < 1090 and x+w > 696 and y+h > 1090 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#高中专业7
if x < 808 and y < 1090 and x+w > 808 and y+h > 1090 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#高中学位8
if x < 931 and y < 1090 and x+w > 931 and y+h > 1090 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#高中起止时间9
if x < 1060 and y < 1087 and x+w > 1060 and y+h > 1087 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#高中是否毕业10
#提取是、否选项旁的正方形框
if jiaozheng == 1 or (len(docu_num) == 9 and (docu_num[6] == '2' or docu_num[6] == '3')) or (len(docu_num) == 8 and ((docu_num[5] == '3' and (docu_num[6] == '3' or (docu_num[6] == '3' and (docu_num[7] == '5' or docu_num[7] == '6' or docu_num[7] == '7' or docu_num[7] == '8' or docu_num[7] == '9')) or docu_num[6] == '4' or docu_num[6] == '5' or docu_num[6] == '7' or docu_num[6] == '8' or docu_num[6] == '9')) or docu_num[5] == '4')):
gaozhong_roi_left = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.2*h/3), int(0.18*w+x):int(0.28*w+x)]
gaozhong_roi_right = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.2*h/3), int(0.59*w+x):int(0.69*w+x)]
cv.imwrite('gaozhong_roi_left.jpg', gaozhong_roi_left)
cv.imwrite('gaozhong_roi_right.jpg', gaozhong_roi_right)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.18*w+x),int(y+h/3.5)),(int(0.28*w+x),int(y+2.2*h/3)),(255,0,0),1)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.59*w+x),int(y+h/3.5)),(int(0.69*w+x),int(y+2.2*h/3)),(255,0,0),1)
else:
gaozhong_roi_left = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.2*h/3), int(0.28*w+x):int(0.38*w+x)]
gaozhong_roi_right = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.2*h/3), int(0.51*w+x):int(0.61*w+x)]
cv.imwrite('gaozhong_roi_left.jpg', gaozhong_roi_left)
cv.imwrite('gaozhong_roi_right.jpg', gaozhong_roi_right)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.28*w+x),int(y+h/3.5)),(int(0.38*w+x),int(y+2.2*h/3)),(255,0,0),1)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.51*w+x),int(y+h/3.5)),(int(0.61*w+x),int(y+2.2*h/3)),(255,0,0),1)
if x < 486 and y < 1130 and x+w > 486 and y+h > 1130 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#大专学校名称11
if x < 696 and y < 1130 and x+w > 696 and y+h > 1130 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#大专专业12
if x < 808 and y < 1130 and x+w > 808 and y+h > 1130 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#大专学位13
if x < 931 and y < 1130 and x+w > 931 and y+h > 1130 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#大专起止时间14
if x < 1060 and y < 1127 and x+w > 1060 and y+h > 1127 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#大专是否毕业15
#提取是、否选项旁的正方形框
if jiaozheng == 1 or (len(docu_num) == 9 and (docu_num[6] == '2' or docu_num[6] == '3')) or (len(docu_num) == 8 and ((docu_num[5] == '3' and (docu_num[6] == '3' or (docu_num[6] == '3' and (docu_num[7] == '5' or docu_num[7] == '6' or docu_num[7] == '7' or docu_num[7] == '8' or docu_num[7] == '9')) or docu_num[6] == '4' or docu_num[6] == '5' or docu_num[6] == '7' or docu_num[6] == '8' or docu_num[6] == '9')) or docu_num[5] == '4')):
dazhuan_roi_left = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.2*h/3), int(0.18*w+x):int(0.28*w+x)]
dazhuan_roi_right = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.2*h/3), int(0.59*w+x):int(0.69*w+x)]
cv.imwrite('dazhuan_roi_left.jpg', dazhuan_roi_left)
cv.imwrite('dazhuan_roi_right.jpg', dazhuan_roi_right)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.18*w+x),int(y+h/3.5)),(int(0.28*w+x),int(y+2.2*h/3)),(255,0,0),1)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.59*w+x),int(y+h/3.5)),(int(0.69*w+x),int(y+2.2*h/3)),(255,0,0),1)
else:
dazhuan_roi_left = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.2*h/3), int(0.28*w+x):int(0.38*w+x)]
dazhuan_roi_right = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.2*h/3), int(0.51*w+x):int(0.61*w+x)]
cv.imwrite('dazhuan_roi_left.jpg', dazhuan_roi_left)
cv.imwrite('dazhuan_roi_right.jpg', dazhuan_roi_right)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.28*w+x),int(y+h/3.5)),(int(0.38*w+x),int(y+2.2*h/3)),(255,0,0),1)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.51*w+x),int(y+h/3.5)),(int(0.61*w+x),int(y+2.2*h/3)),(255,0,0),1)
if x < 486 and y < 1170 and x+w > 486 and y+h > 1170 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#本科学校名称16
if x < 696 and y < 1170 and x+w > 696 and y+h > 1170 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#本科专业17
if x < 808 and y < 1170 and x+w > 808 and y+h > 1170 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#本科学位18
if x < 931 and y < 1170 and x+w > 931 and y+h > 1170 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#本科起止时间19
if x < 1060 and y < 1167 and x+w > 1060 and y+h > 1167 or something_missing == 1:
if something_missing == 1:#特殊情况下表格矩形的提取
x = x_rem
y = y_rem + 40
w = w_rem
h = h_rem
else:
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#本科是否毕业20
#提取是、否选项旁的正方形框
if jiaozheng == 1 or (len(docu_num) == 9 and (docu_num[6] == '2' or docu_num[6] == '3')) or (len(docu_num) == 8 and ((docu_num[5] == '3' and (docu_num[6] == '3' or (docu_num[6] == '3' and (docu_num[7] == '5' or docu_num[7] == '6' or docu_num[7] == '7' or docu_num[7] == '8' or docu_num[7] == '9')) or docu_num[6] == '4' or docu_num[6] == '5' or docu_num[6] == '7' or docu_num[6] == '8' or docu_num[6] == '9')) or docu_num[5] == '4')):
benke_roi_left = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.2*h/3), int(0.18*w+x):int(0.28*w+x)]
benke_roi_right = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.2*h/3), int(0.59*w+x):int(0.69*w+x)]
cv.imwrite('benke_roi_left.jpg', benke_roi_left)
cv.imwrite('benke_roi_right.jpg', benke_roi_right)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.18*w+x),int(y+h/3.5)),(int(0.28*w+x),int(y+2.2*h/3)),(255,0,0),1)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.59*w+x),int(y+h/3.5)),(int(0.69*w+x),int(y+2.2*h/3)),(255,0,0),1)
else:
benke_roi_left = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.2*h/3), int(0.28*w+x):int(0.38*w+x)]
benke_roi_right = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.2*h/3), int(0.51*w+x):int(0.61*w+x)]
cv.imwrite('benke_roi_left.jpg', benke_roi_left)
cv.imwrite('benke_roi_right.jpg', benke_roi_right)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.28*w+x),int(y+h/3.5)),(int(0.38*w+x),int(y+2.2*h/3)),(255,0,0),1)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.51*w+x),int(y+h/3.5)),(int(0.61*w+x),int(y+2.2*h/3)),(255,0,0),1)
if x < 486 and y < 1210 and x+w > 486 and y+h > 1210 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#研究生学校名称21
if x < 696 and y < 1210 and x+w > 696 and y+h > 1210 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#研究生专业22
if x < 808 and y < 1210 and x+w > 808 and y+h > 1210 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#研究生学位23
if x < 931 and y < 1210 and x+w > 931 and y+h > 1210 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#研究生起止时间24
if x < 1060 and y < 1207 and x+w > 1060 and y+h > 1207 or something_missing == 1:
if something_missing == 1:#特殊情况下表格矩形的提取
x = x_rem
y = y_rem + 80
w = w_rem
h = h_rem
else:
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#研究生是否毕业25
#提取是、否选项旁的正方形框
if jiaozheng == 1 or (len(docu_num) == 9 and (docu_num[6] == '2' or docu_num[6] == '3')) or (len(docu_num) == 8 and ((docu_num[5] == '3' and (docu_num[6] == '3' or (docu_num[6] == '3' and (docu_num[7] == '5' or docu_num[7] == '6' or docu_num[7] == '7' or docu_num[7] == '8' or docu_num[7] == '9')) or docu_num[6] == '4' or docu_num[6] == '5' or docu_num[6] == '7' or docu_num[6] == '8' or docu_num[6] == '9')) or docu_num[5] == '4')):
yanjiu_roi_left = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.2*h/3), int(0.18*w+x):int(0.28*w+x)]
yanjiu_roi_right = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.2*h/3), int(0.59*w+x):int(0.69*w+x)]
cv.imwrite('yanjiu_roi_left.jpg', yanjiu_roi_left)
cv.imwrite('yanjiu_roi_right.jpg', yanjiu_roi_right)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.18*w+x),int(y+h/3.5)),(int(0.28*w+x),int(y+2.2*h/3)),(255,0,0),1)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.59*w+x),int(y+h/3.5)),(int(0.69*w+x),int(y+2.2*h/3)),(255,0,0),1)
else:
yanjiu_roi_left = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.2*h/3), int(0.28*w+x):int(0.38*w+x)]
yanjiu_roi_right = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.2*h/3), int(0.51*w+x):int(0.61*w+x)]
cv.imwrite('yanjiu_roi_left.jpg', yanjiu_roi_left)
cv.imwrite('yanjiu_roi_right.jpg', yanjiu_roi_right)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.28*w+x),int(y+h/3.5)),(int(0.38*w+x),int(y+2.2*h/3)),(255,0,0),1)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.51*w+x),int(y+h/3.5)),(int(0.61*w+x),int(y+2.2*h/3)),(255,0,0),1)
#特殊情况下表格矩形的提取
if need_stronger == 1:
cv.rectangle(shrinkTwoTimesTranslation,(673,385),(740,420),(0,0,255),1)#性别
cv.rectangle(shrinkTwoTimesTranslation,(845,385),(938,420),(0,0,255),1)#民族
cv.rectangle(shrinkTwoTimesTranslation,(673,425),(720,460),(0,0,255),1)#体重
cv.rectangle(shrinkTwoTimesTranslation,(845,425),(938,465),(0,0,255),1)#血型
cv.rectangle(shrinkTwoTimesTranslation,(845,470),(938,510),(0,0,255),1)#籍贯
cv.rectangle(shrinkTwoTimesTranslation,(973,1095),(1153,1135),(0,0,255),1)#高中是否毕业
x = 973
y = 1095
w = 1153 - 973
h = 1135 - 1095
gaozhong_roi_left = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.2*h/3), int(0.28*w+x):int(0.38*w+x)]
gaozhong_roi_right = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.2*h/3), int(0.51*w+x):int(0.61*w+x)]
cv.imwrite('gaozhong_roi_left.jpg', gaozhong_roi_left)
cv.imwrite('gaozhong_roi_right.jpg', gaozhong_roi_right)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.28*w+x),int(y+h/3.5)),(int(0.38*w+x),int(y+2.2*h/3)),(255,0,0),1)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.51*w+x),int(y+h/3.5)),(int(0.61*w+x),int(y+2.2*h/3)),(255,0,0),1)
cv.rectangle(shrinkTwoTimesTranslation,(973,1135),(1153,1175),(0,0,255),1)
x = 973
y = 1135
w = 1153 - 973
h = 1175 - 1135
dazhuan_roi_left = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.2*h/3), int(0.28*w+x):int(0.38*w+x)]
dazhuan_roi_right = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.2*h/3), int(0.51*w+x):int(0.61*w+x)]
cv.imwrite('dazhuan_roi_left.jpg', dazhuan_roi_left)
cv.imwrite('dazhuan_roi_right.jpg', dazhuan_roi_right)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.28*w+x),int(y+h/3.5)),(int(0.38*w+x),int(y+2.2*h/3)),(255,0,0),1)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.51*w+x),int(y+h/3.5)),(int(0.61*w+x),int(y+2.2*h/3)),(255,0,0),1)
cv.rectangle(shrinkTwoTimesTranslation,(973,1175),(1153,1215),(0,0,255),1)
x = 973
y = 1175
w = 1153 - 973
h = 1215 - 1175
benke_roi_left = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.2*h/3), int(0.28*w+x):int(0.38*w+x)]
benke_roi_right = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.2*h/3), int(0.51*w+x):int(0.61*w+x)]
cv.imwrite('benke_roi_left.jpg', benke_roi_left)
cv.imwrite('benke_roi_right.jpg', benke_roi_right)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.28*w+x),int(y+h/3.5)),(int(0.38*w+x),int(y+2.2*h/3)),(255,0,0),1)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.51*w+x),int(y+h/3.5)),(int(0.61*w+x),int(y+2.2*h/3)),(255,0,0),1)
cv.rectangle(shrinkTwoTimesTranslation,(973,1220),(1153,1260),(0,0,255),1)
x = 973
y = 1220
w = 1153 - 973
h = 1260 - 1220
yanjiu_roi_left = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.2*h/3), int(0.28*w+x):int(0.38*w+x)]
yanjiu_roi_right = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.2*h/3), int(0.51*w+x):int(0.61*w+x)]
cv.imwrite('yanjiu_roi_left.jpg', yanjiu_roi_left)
cv.imwrite('yanjiu_roi_right.jpg', yanjiu_roi_right)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.28*w+x),int(y+h/3.5)),(int(0.38*w+x),int(y+2.2*h/3)),(255,0,0),1)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.51*w+x),int(y+h/3.5)),(int(0.61*w+x),int(y+2.2*h/3)),(255,0,0),1)
#测试各信息的大致位置
#cv.circle(shrinkTwoTimesTranslation, (700, 335), 3,(255,0,0),3)
#cv.circle(shrinkTwoTimesTranslation, (75, 1581), 3,(255,0,0),3)
#cv.rectangle(shrinkTwoTimesTranslation,(663,360),(740,400),(255,0,0),1)#性别
#cv.rectangle(shrinkTwoTimesTranslation,(835,360),(928,400),(255,0,0),1)#民族
#cv.rectangle(shrinkTwoTimesTranslation,(663,402),(710,442),(255,0,0),1)#体重
#cv.rectangle(shrinkTwoTimesTranslation,(835,402),(928,442),(255,0,0),1)#血型
#cv.rectangle(shrinkTwoTimesTranslation,(835,443),(948,482),(255,0,0),1)#籍贯
#cv.rectangle(shrinkTwoTimesTranslation,(345,1075),(627,1115),(255,0,0),1)#高中学校名称
#cv.rectangle(shrinkTwoTimesTranslation,(628,1075),(765,1115),(255,0,0),1)#高中专业
#cv.rectangle(shrinkTwoTimesTranslation,(766,1075),(850,1115),(255,0,0),1)#高中学位
#cv.rectangle(shrinkTwoTimesTranslation,(851,1075),(1011,1115),(255,0,0),1)#高中起止时间
#cv.rectangle(shrinkTwoTimesTranslation,(971,1070),(1150,1110),(255,0,0),1)#高中是否毕业
if table_style == 2:
request_info = (770, 150, 1150-770, 300-150)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(770,150),(1150,300),(255,0,0),1)#登记表编号0
for j in range(0,len(small_rects)):
(x, y, w, h) = small_rects[j]
if x < 700 and y < 335 and x+w > 700 and y+h > 335 :#350-20
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#性别1
if x < 885 and y < 335 and x+w > 885 and y+h > 335 :#x+5
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#民族2
if x < 685 and y < 377 and x+w > 685 and y+h > 377 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#体重3
if x < 885 and y < 377 and x+w > 885 and y+h > 377 :#x+5
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(0,0,255),1)#血型4
if x < 890 and y < 417 and x+w > 890 and y+h > 417 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#籍贯5
if x < 486 and y < 1045 and x+w > 486 and y+h > 1045 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#高中学校名称6
if x < 696 and y < 1045 and x+w > 696 and y+h > 1045 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#高中专业7
if x < 808 and y < 1045 and x+w > 808 and y+h > 1045 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#高中学位8
if len(docu_num) == 9 and (docu_num[6] == '2' and (docu_num[7] == '6' or docu_num[7] == '8' or docu_num[7] == '9')):
y_xiuzheng = 1090
else:
y_xiuzheng = 1055
if x < 931 and y < y_xiuzheng and x+w > 931 and y+h > y_xiuzheng :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#高中起止时间9
if x < 1060 and y < y_xiuzheng and x+w > 1060 and y+h > y_xiuzheng :#y+10
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#高中是否毕业10
if len(docu_num) == 9 and (docu_num[6] == '2' and (docu_num[7] == '6' or docu_num[7] == '8' or docu_num[7] == '9')) or (docu_num[6] == '3' and docu_num[8] == '9'):
gaozhong_roi_left = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.2*h/3), int(0.22*w+x):int(0.32*w+x)]
gaozhong_roi_right = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.2*h/3), int(0.55*w+x):int(0.65*w+x)]
cv.imwrite('gaozhong_roi_left.jpg', gaozhong_roi_left)
cv.imwrite('gaozhong_roi_right.jpg', gaozhong_roi_right)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.22*w+x),int(y+h/3.5)),(int(0.32*w+x),int(y+2.2*h/3)),(255,0,0),1)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.55*w+x),int(y+h/3.5)),(int(0.65*w+x),int(y+2.2*h/3)),(255,0,0),1)
else:
gaozhong_roi_left = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.2*h/3), int(0.28*w+x):int(0.38*w+x)]
gaozhong_roi_right = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.2*h/3), int(0.51*w+x):int(0.61*w+x)]
cv.imwrite('gaozhong_roi_left.jpg', gaozhong_roi_left)
cv.imwrite('gaozhong_roi_right.jpg', gaozhong_roi_right)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.28*w+x),int(y+h/3.5)),(int(0.38*w+x),int(y+2.2*h/3)),(255,0,0),1)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.51*w+x),int(y+h/3.5)),(int(0.61*w+x),int(y+2.2*h/3)),(255,0,0),1)
if x < 486 and y < 1085 and x+w > 486 and y+h > 1085 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#大专学校名称11
if x < 696 and y < 1085 and x+w > 696 and y+h > 1085 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#大专专业12
if x < 808 and y < 1085 and x+w > 808 and y+h > 1085 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#大专学位13
if len(docu_num) == 9 and (docu_num[6] == '2' and (docu_num[7] == '6' or docu_num[7] == '8' or docu_num[7] == '9')):
y_xiuzheng = 1140
else:
y_xiuzheng = 1095
if x < 931 and y < y_xiuzheng and x+w > 931 and y+h > y_xiuzheng :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#大专起止时间14
if x < 1060 and y < y_xiuzheng and x+w > 1060 and y+h > y_xiuzheng :#y+10
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#大专是否毕业15
if len(docu_num) == 9 and (docu_num[6] == '2' and (docu_num[7] == '6' or docu_num[7] == '8' or docu_num[7] == '9')) or (docu_num[6] == '3' and docu_num[8] == '9'):
dazhuan_roi_left = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.2*h/3), int(0.22*w+x):int(0.32*w+x)]
dazhuan_roi_right = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.2*h/3), int(0.55*w+x):int(0.65*w+x)]
cv.imwrite('dazhuan_roi_left.jpg', dazhuan_roi_left)
cv.imwrite('dazhuan_roi_right.jpg', dazhuan_roi_right)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.22*w+x),int(y+h/3.5)),(int(0.32*w+x),int(y+2.2*h/3)),(255,0,0),1)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.55*w+x),int(y+h/3.5)),(int(0.65*w+x),int(y+2.2*h/3)),(255,0,0),1)
else:
dazhuan_roi_left = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.2*h/3), int(0.28*w+x):int(0.38*w+x)]
dazhuan_roi_right = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.2*h/3), int(0.51*w+x):int(0.61*w+x)]
cv.imwrite('dazhuan_roi_left.jpg', dazhuan_roi_left)
cv.imwrite('dazhuan_roi_right.jpg', dazhuan_roi_right)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.28*w+x),int(y+h/3.5)),(int(0.38*w+x),int(y+2.2*h/3)),(255,0,0),1)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.51*w+x),int(y+h/3.5)),(int(0.61*w+x),int(y+2.2*h/3)),(255,0,0),1)
if x < 486 and y < 1125 and x+w > 486 and y+h > 1125 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#本科学校名称16
if x < 696 and y < 1125 and x+w > 696 and y+h > 1125 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#本科专业17
if x < 808 and y < 1125 and x+w > 808 and y+h > 1125 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#本科学位18
if len(docu_num) == 9 and (docu_num[6] == '2' and (docu_num[7] == '6' or docu_num[7] == '8' or docu_num[7] == '9')):
y_xiuzheng = 1190
else:
y_xiuzheng = 1135
if x < 931 and y < y_xiuzheng and x+w > 931 and y+h > y_xiuzheng :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#本科起止时间19
if x < 1060 and y < y_xiuzheng and x+w > 1060 and y+h > y_xiuzheng :#y+10
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#本科是否毕业20
if len(docu_num) == 9 and (docu_num[6] == '2' and (docu_num[7] == '6' or docu_num[7] == '8' or docu_num[7] == '9')) or (docu_num[6] == '3' and docu_num[8] == '9'):
benke_roi_left = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.2*h/3), int(0.22*w+x):int(0.32*w+x)]
benke_roi_right = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.2*h/3), int(0.55*w+x):int(0.65*w+x)]
cv.imwrite('benke_roi_left.jpg', benke_roi_left)
cv.imwrite('benke_roi_right.jpg', benke_roi_right)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.22*w+x),int(y+h/3.5)),(int(0.32*w+x),int(y+2.2*h/3)),(255,0,0),1)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.55*w+x),int(y+h/3.5)),(int(0.65*w+x),int(y+2.2*h/3)),(255,0,0),1)
else:
benke_roi_left = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.2*h/3), int(0.28*w+x):int(0.38*w+x)]
benke_roi_right = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.2*h/3), int(0.51*w+x):int(0.61*w+x)]
cv.imwrite('benke_roi_left.jpg', benke_roi_left)
cv.imwrite('benke_roi_right.jpg', benke_roi_right)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.28*w+x),int(y+h/3.5)),(int(0.38*w+x),int(y+2.2*h/3)),(255,0,0),1)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.51*w+x),int(y+h/3.5)),(int(0.61*w+x),int(y+2.2*h/3)),(255,0,0),1)
if x < 486 and y < 1165 and x+w > 486 and y+h > 1165 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#研究生学校名称21
if x < 696 and y < 1165 and x+w > 696 and y+h > 1165 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#研究生专业22
if x < 808 and y < 1165 and x+w > 808 and y+h > 1165 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#研究生学位23
if len(docu_num) == 9 and (docu_num[6] == '2' and (docu_num[7] == '6' or docu_num[7] == '8' or docu_num[7] == '9')):
y_xiuzheng = 1230
else:
y_xiuzheng = 1175
if x < 931 and y < y_xiuzheng and x+w > 931 and y+h > y_xiuzheng :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#研究生起止时间24
if x < 1060 and y < y_xiuzheng and x+w > 1060 and y+h > y_xiuzheng :#y+10
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#研究生是否毕业25
if len(docu_num) == 9 and (docu_num[6] == '2' and (docu_num[7] == '6' or docu_num[7] == '8' or docu_num[7] == '9')) or (docu_num[6] == '3' and docu_num[8] == '9'):
yanjiu_roi_left = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.2*h/3), int(0.22*w+x):int(0.32*w+x)]
yanjiu_roi_right = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.2*h/3), int(0.55*w+x):int(0.65*w+x)]
cv.imwrite('yanjiu_roi_left.jpg', yanjiu_roi_left)
cv.imwrite('yanjiu_roi_right.jpg', yanjiu_roi_right)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.22*w+x),int(y+h/3.5)),(int(0.32*w+x),int(y+2.2*h/3)),(255,0,0),1)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.55*w+x),int(y+h/3.5)),(int(0.65*w+x),int(y+2.2*h/3)),(255,0,0),1)
else:
yanjiu_roi_left = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.2*h/3), int(0.28*w+x):int(0.38*w+x)]
yanjiu_roi_right = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.2*h/3), int(0.51*w+x):int(0.61*w+x)]
cv.imwrite('yanjiu_roi_left.jpg', yanjiu_roi_left)
cv.imwrite('yanjiu_roi_right.jpg', yanjiu_roi_right)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.28*w+x),int(y+h/3.5)),(int(0.38*w+x),int(y+2.2*h/3)),(255,0,0),1)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.51*w+x),int(y+h/3.5)),(int(0.61*w+x),int(y+2.2*h/3)),(255,0,0),1)
if table_style == 3:
request_info = (970, 50, 1200-970, 200-50)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(970,50),(1200,200),(255,0,0),1)#登记表编号0
for j in range(0,len(small_rects)):
(x, y, w, h) = small_rects[j]
if x < 724 and y < 316 and x+w > 724 and y+h > 316 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#性别1
if x < 960 and y < 316 and x+w > 960 and y+h > 316 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#民族2
if x < 724 and y < 363 and x+w > 724 and y+h > 363 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#体重3
if x < 960 and y < 363 and x+w > 960 and y+h > 363 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#血型4
if x < 960 and y < 410 and x+w > 960 and y+h > 410 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#籍贯5
if x < 981 and y < 1089 and x+w > 981 and y+h > 1089 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#高中起止时间9
if x < 1105 and y < 1089 and x+w > 1105 and y+h > 1089 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#高中是否毕业10
if docu_num[5] == '3' and docu_num[6] == '8':
gaozhong_roi_left = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.1*h/3), int(0.19*w+x):int(0.29*w+x)]
gaozhong_roi_right = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.1*h/3), int(0.59*w+x):int(0.69*w+x)]
cv.imwrite('gaozhong_roi_left.jpg', gaozhong_roi_left)
cv.imwrite('gaozhong_roi_right.jpg', gaozhong_roi_right)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.19*w+x),int(y+h/3.5)),(int(0.29*w+x),int(y+2.1*h/3)),(255,0,0),1)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.59*w+x),int(y+h/3.5)),(int(0.69*w+x),int(y+2.1*h/3)),(255,0,0),1)
else:
gaozhong_roi_left = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.1*h/3), int(0.23*w+x):int(0.33*w+x)]
gaozhong_roi_right = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.1*h/3), int(0.56*w+x):int(0.66*w+x)]
cv.imwrite('gaozhong_roi_left.jpg', gaozhong_roi_left)
cv.imwrite('gaozhong_roi_right.jpg', gaozhong_roi_right)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.23*w+x),int(y+h/3.5)),(int(0.33*w+x),int(y+2.1*h/3)),(255,0,0),1)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.56*w+x),int(y+h/3.5)),(int(0.66*w+x),int(y+2.1*h/3)),(255,0,0),1)
if x < 981 and y < 1137 and x+w > 981 and y+h > 1137 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#大专起止时间14
if x < 1105 and y < 1137 and x+w > 1105 and y+h > 1137 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#大专是否毕业15
if docu_num[5] == '3' and docu_num[6] == '8':
dazhuan_roi_left = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.1*h/3), int(0.19*w+x):int(0.29*w+x)]
dazhuan_roi_right = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.1*h/3), int(0.59*w+x):int(0.69*w+x)]
cv.imwrite('dazhuan_roi_left.jpg', dazhuan_roi_left)
cv.imwrite('dazhuan_roi_right.jpg', dazhuan_roi_right)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.19*w+x),int(y+h/3.5)),(int(0.29*w+x),int(y+2.1*h/3)),(255,0,0),1)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.59*w+x),int(y+h/3.5)),(int(0.69*w+x),int(y+2.1*h/3)),(255,0,0),1)
else:
dazhuan_roi_left = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.1*h/3), int(0.23*w+x):int(0.33*w+x)]
dazhuan_roi_right = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.1*h/3), int(0.56*w+x):int(0.66*w+x)]
cv.imwrite('dazhuan_roi_left.jpg', dazhuan_roi_left)
cv.imwrite('dazhuan_roi_right.jpg', dazhuan_roi_right)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.23*w+x),int(y+h/3.5)),(int(0.33*w+x),int(y+2.1*h/3)),(255,0,0),1)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.56*w+x),int(y+h/3.5)),(int(0.66*w+x),int(y+2.1*h/3)),(255,0,0),1)
if x < 981 and y < 1185 and x+w > 981 and y+h > 1185 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#本科起止时间19
if x < 1105 and y < 1185 and x+w > 1105 and y+h > 1185 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#本科是否毕业20
if docu_num[5] == '3' and docu_num[6] == '8':
benke_roi_left = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.1*h/3), int(0.19*w+x):int(0.29*w+x)]
benke_roi_right = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.1*h/3), int(0.59*w+x):int(0.69*w+x)]
cv.imwrite('benke_roi_left.jpg', benke_roi_left)
cv.imwrite('benke_roi_right.jpg', benke_roi_right)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.19*w+x),int(y+h/3.5)),(int(0.29*w+x),int(y+2.1*h/3)),(255,0,0),1)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.59*w+x),int(y+h/3.5)),(int(0.69*w+x),int(y+2.1*h/3)),(255,0,0),1)
else:
benke_roi_left = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.1*h/3), int(0.23*w+x):int(0.33*w+x)]
benke_roi_right = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.1*h/3), int(0.56*w+x):int(0.66*w+x)]
cv.imwrite('benke_roi_left.jpg', benke_roi_left)
cv.imwrite('benke_roi_right.jpg', benke_roi_right)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.23*w+x),int(y+h/3.5)),(int(0.33*w+x),int(y+2.1*h/3)),(255,0,0),1)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.56*w+x),int(y+h/3.5)),(int(0.66*w+x),int(y+2.1*h/3)),(255,0,0),1)
if x < 981 and y < 1233 and x+w > 981 and y+h > 1233 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#研究生起止时间24
if x < 1105 and y < 1233 and x+w > 1105 and y+h > 1233 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#研究生是否毕业25
if docu_num[5] == '3' and docu_num[6] == '8':
yanjiu_roi_left = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.1*h/3), int(0.19*w+x):int(0.29*w+x)]
yanjiu_roi_right = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.1*h/3), int(0.59*w+x):int(0.69*w+x)]
cv.imwrite('yanjiu_roi_left.jpg', yanjiu_roi_left)
cv.imwrite('yanjiu_roi_right.jpg', yanjiu_roi_right)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.19*w+x),int(y+h/3.5)),(int(0.29*w+x),int(y+2.1*h/3)),(255,0,0),1)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.59*w+x),int(y+h/3.5)),(int(0.69*w+x),int(y+2.1*h/3)),(255,0,0),1)
else:
yanjiu_roi_left = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.1*h/3), int(0.23*w+x):int(0.33*w+x)]
yanjiu_roi_right = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.1*h/3), int(0.56*w+x):int(0.66*w+x)]
cv.imwrite('yanjiu_roi_left.jpg', yanjiu_roi_left)
cv.imwrite('yanjiu_roi_right.jpg', yanjiu_roi_right)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.23*w+x),int(y+h/3.5)),(int(0.33*w+x),int(y+2.1*h/3)),(255,0,0),1)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.56*w+x),int(y+h/3.5)),(int(0.66*w+x),int(y+2.1*h/3)),(255,0,0),1)
if table_style == 4:
request_info = (970, 50, 1200-970, 200-50)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(970,50),(1200,200),(255,0,0),1)#登记表编号0
for j in range(0,len(small_rects)):
(x, y, w, h) = small_rects[j]
if x < 724 and y < 292 and x+w > 724 and y+h > 292 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#性别1
if x < 960 and y < 292 and x+w > 960 and y+h > 292 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#民族2
if x < 724 and y < 339 and x+w > 724 and y+h > 339 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#体重3
if x < 960 and y < 339 and x+w > 960 and y+h > 339 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#血型4
if x < 960 and y < 386 and x+w > 960 and y+h > 386 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#籍贯5
if x < 981 and y < 1094 and x+w > 981 and y+h > 1094 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#高中起止时间9
if x < 1105 and y < 1094 and x+w > 1105 and y+h > 1094 :#y-15
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#高中是否毕业10
gaozhong_roi_left = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.1*h/3), int(0.23*w+x):int(0.33*w+x)]
gaozhong_roi_right = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.1*h/3), int(0.56*w+x):int(0.66*w+x)]
cv.imwrite('gaozhong_roi_left.jpg', gaozhong_roi_left)
cv.imwrite('gaozhong_roi_right.jpg', gaozhong_roi_right)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.23*w+x),int(y+h/3.5)),(int(0.33*w+x),int(y+2.1*h/3)),(255,0,0),1)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.56*w+x),int(y+h/3.5)),(int(0.66*w+x),int(y+2.1*h/3)),(255,0,0),1)
if x < 981 and y < 1142 and x+w > 981 and y+h > 1142 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#大专起止时间14
if x < 1105 and y < 1142 and x+w > 1105 and y+h > 1142 :#y-15
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#大专是否毕业15
dazhuan_roi_left = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.1*h/3), int(0.23*w+x):int(0.33*w+x)]
dazhuan_roi_right = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.1*h/3), int(0.56*w+x):int(0.66*w+x)]
cv.imwrite('dazhuan_roi_left.jpg', dazhuan_roi_left)
cv.imwrite('dazhuan_roi_right.jpg', dazhuan_roi_right)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.23*w+x),int(y+h/3.5)),(int(0.33*w+x),int(y+2.1*h/3)),(255,0,0),1)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.56*w+x),int(y+h/3.5)),(int(0.66*w+x),int(y+2.1*h/3)),(255,0,0),1)
if x < 981 and y < 1190 and x+w > 981 and y+h > 1190 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#本科起止时间19
if x < 1105 and y < 1190 and x+w > 1105 and y+h > 1190 :#y-15
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#本科是否毕业20
benke_roi_left = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.1*h/3), int(0.23*w+x):int(0.33*w+x)]
benke_roi_right = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.1*h/3), int(0.56*w+x):int(0.66*w+x)]
cv.imwrite('benke_roi_left.jpg', benke_roi_left)
cv.imwrite('benke_roi_right.jpg', benke_roi_right)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.23*w+x),int(y+h/3.5)),(int(0.33*w+x),int(y+2.1*h/3)),(255,0,0),1)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.56*w+x),int(y+h/3.5)),(int(0.66*w+x),int(y+2.1*h/3)),(255,0,0),1)
if x < 981 and y < 1238 and x+w > 981 and y+h > 1238 :
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#研究生起止时间24
if x < 1105 and y < 1238 and x+w > 1105 and y+h > 1238 :#y-15
request_info = (x, y, w, h)
request_info_set.append(request_info)
cv.rectangle(shrinkTwoTimesTranslation,(x,y),(x+w,y+h),(255,0,0),1)#研究生是否毕业25
yanjiu_roi_left = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.1*h/3), int(0.23*w+x):int(0.33*w+x)]
yanjiu_roi_right = shrinkTwoTimesTranslation[int(y+h/3.5):int(y+2.1*h/3), int(0.56*w+x):int(0.66*w+x)]
cv.imwrite('yanjiu_roi_left.jpg', yanjiu_roi_left)
cv.imwrite('yanjiu_roi_right.jpg', yanjiu_roi_right)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.23*w+x),int(y+h/3.5)),(int(0.33*w+x),int(y+2.1*h/3)),(255,0,0),1)
cv.rectangle(shrinkTwoTimesTranslation,(int(0.56*w+x),int(y+h/3.5)),(int(0.66*w+x),int(y+2.1*h/3)),(255,0,0),1)
#cv.rectangle(shrinkTwoTimesTranslation,(663,269),(786,315),(255,0,0),1)#性别
#cv.rectangle(shrinkTwoTimesTranslation,(900,269),(1020,315),(255,0,0),1)#民族
#cv.rectangle(shrinkTwoTimesTranslation,(663,316),(786,362),(255,0,0),1)#体重
#cv.rectangle(shrinkTwoTimesTranslation,(900,316),(1020,362),(255,0,0),1)#血型
#cv.rectangle(shrinkTwoTimesTranslation,(900,363),(1020,409),(255,0,0),1)#籍贯
#cv.rectangle(shrinkTwoTimesTranslation,(1016,1065),(1195,1113),(255,0,0),1)#高中是否毕业
#登记表编号,性别,民族,体重,血型,籍贯,高中学校名称,高中专业,高中学位,高中起止时间,高中是否毕业,大专学校名称,大专专业,大专学位,大专起止时间,大专是否毕业,本科学校名称,本科专业,本科学位,本科起止时间,本科是否毕业,研究生学校名称,研究生专业,研究生学位,研究生起止时间,研究生是否毕业,学校名称（其它）,专业（其它）,学位（其它）,起止时间（其它）,是否毕业（其它）
cv.imwrite('image_correct.jpg', shrinkTwoTimesTranslation)#关键信息框重点标注的矫正图像
########### 去除噪点Filter ###########
th2 = cv.medianBlur(th2,5)#5
horizontalStructure = cv.getStructuringElement(cv.MORPH_RECT, (2, 2))#2,2
th2 = cv.erode(th2,horizontalStructure,iterations = 1)
#horizontalStructure = cv.getStructuringElement(cv.MORPH_RECT, (1, 3))#2,2
#th2 = cv.dilate(th2,horizontalStructure,iterations = 1)