How to implement batch data extraction through Python
Configuration requirements
1.ImageMagick
2.tesseract-OCR
3.Python3.7
4.from PIL import Image as PI
5.import io
6.import os
7.import pyocr.builders
8.from cnocr import CnOcr
import The data is converted into a digital format. Based on this, we need to first complete the conversion of uppercase Chinese characters and numbers.
def chineseNumber2Int(strNum: str): result = 0 temp = 1 # 存放一个单位的数字如:十万 count = 0 # 判断是否有chArr cnArr = ['壹', '贰', '叁', '肆', '伍', '陆', '柒', '捌', '玖'] chArr = ['拾', '佰', '仟', '万', '亿'] for i in range(len(strNum)): b = True c = strNum[i] for j in range(len(cnArr)): if c == cnArr[j]: if count != 0: result += temp count = 0 temp = j + 1 b = False break if b: for j in range(len(chArr)): if c == chArr[j]: if j == 0: temp *= 10 elif j == 1: temp *= 100 elif j == 2: temp *= 1000 elif j == 3: temp *= 10000 elif j == 4: temp *= 100000000 count += 1 if i == len(strNum) - 1: result += temp return result
The above code can be used to convert uppercase letters and numbers. For example, input "Twenty thousand yuan" to export "200000", and then convert it into numbers to greatly simplify the table. Operations can also be beneficial to data archiving while completing table operations.
As shown in the picture, the small black dot is where the mouse is, and the lower left corner of the drawing software is its coordinates.
Extract the issue date
def text1(new_img): #提取出票日期 left = 80 top = 143 right = 162 bottom = 162 image_text1 = new_img.crop((left, top, right, bottom)) #展示图片 #image_text1.show() txt1 = tool.image_to_string(image_text1) print(txt1) return str(txt1)
Withdraw the amount
def text2(new_img): #提取金额 left = 224 top = 355 right = 585 bottom = 380 image_text2 = new_img.crop((left, top, right, bottom)) #展示图片 #image_text2.show() image_text2.save("img/tmp.png") temp = ocr.ocr("img/tmp.png") temp="".join(temp[0]) txt2=chineseNumber2Int(temp) print(txt2) return txt2
def text3(new_img):
#提取出票人
left = 177
top = 207
right = 506
bottom = 231
image_text3 = new_img.crop((left, top, right, bottom))
#展示图片
#image_text3.show()
image_text3.save("img/tmp.png")
temp = ocr.ocr("img/tmp.png")
txt3="".join(temp[0])
print(txt3)
return txt3
Copy after login
Extract the payment bankdef text3(new_img): #提取出票人 left = 177 top = 207 right = 506 bottom = 231 image_text3 = new_img.crop((left, top, right, bottom)) #展示图片 #image_text3.show() image_text3.save("img/tmp.png") temp = ocr.ocr("img/tmp.png") txt3="".join(temp[0]) print(txt3) return txt3
def text4(new_img):
#提取付款行
left = 177
top = 274
right = 492
bottom = 311
image_text4 = new_img.crop((left, top, right, bottom))
#展示图片
#image_text4.show()
image_text4.save("img/tmp.png")
temp = ocr.ocr("img/tmp.png")
txt4="".join(temp[0])
print(txt4)
return txt4
Copy after login
Extract the bill of exchange arrival datedef text4(new_img): #提取付款行 left = 177 top = 274 right = 492 bottom = 311 image_text4 = new_img.crop((left, top, right, bottom)) #展示图片 #image_text4.show() image_text4.save("img/tmp.png") temp = ocr.ocr("img/tmp.png") txt4="".join(temp[0]) print(txt4) return txt4
def text5(new_img):
#提取汇票到日期
left = 92
top = 166
right = 176
bottom = 184
image_text5 = new_img.crop((left, top, right, bottom))
#展示图片
#image_text5.show()
txt5 = tool.image_to_string(image_text5)
print(txt5)
return txt5
Copy after login
Extract the bill documentdef text5(new_img): #提取汇票到日期 left = 92 top = 166 right = 176 bottom = 184 image_text5 = new_img.crop((left, top, right, bottom)) #展示图片 #image_text5.show() txt5 = tool.image_to_string(image_text5) print(txt5) return txt5
def text6(new_img):
#提取票据号码
left = 598
top = 166
right = 870
bottom = 182
image_text6 = new_img.crop((left, top, right, bottom))
#展示图片
#image_text6.show()
txt6 = tool.image_to_string(image_text6)
print(txt6)
return txt6
Copy after login
After all the data is extracted, we enter the setting process. We need to extract all the bill files first , get their file names and paths. def text6(new_img): #提取票据号码 left = 598 top = 166 right = 870 bottom = 182 image_text6 = new_img.crop((left, top, right, bottom)) #展示图片 #image_text6.show() txt6 = tool.image_to_string(image_text6) print(txt6) return txt6
ocr=CnOcr()
tool = pyocr.get_available_tools()[0]
filePath='img'
img_name=[]
for i,j,name in os.walk(filePath):
img_name=name
Copy after login
After obtaining the complete data, you can import the data into Excel. ocr=CnOcr() tool = pyocr.get_available_tools()[0] filePath='img' img_name=[] for i,j,name in os.walk(filePath): img_name=name
count=1
book = xlwt.Workbook(encoding='utf-8',style_compression=0)
sheet = book.add_sheet('test',cell_overwrite_ok=True)
for i in img_name:
img_url = filePath+"/"+i
with open(img_url, 'rb') as f:
a = f.read()
new_img = PI.open(io.BytesIO(a))
## 写入csv
col = ('年份','出票日期','金额','出票人','付款行全称','汇票到日期','备注')
for j in range(0,7):
sheet.write(0,j,col[j])
book.save('1.csv')
shijian=text1(new_img)
sheet.write(count,0,shijian[0:4])
sheet.write(count,1,shijian[5:])
sheet.write(count,2,text2(new_img))
sheet.write(count,3,text3(new_img))
sheet.write(count,4,text4(new_img))
sheet.write(count,5,text5(new_img))
sheet.write(count,6,text6(new_img))
count = count + 1
Copy after login
At this point, the complete process is over. Attached are all source codescount=1 book = xlwt.Workbook(encoding='utf-8',style_compression=0) sheet = book.add_sheet('test',cell_overwrite_ok=True) for i in img_name: img_url = filePath+"/"+i with open(img_url, 'rb') as f: a = f.read() new_img = PI.open(io.BytesIO(a)) ## 写入csv col = ('年份','出票日期','金额','出票人','付款行全称','汇票到日期','备注') for j in range(0,7): sheet.write(0,j,col[j]) book.save('1.csv') shijian=text1(new_img) sheet.write(count,0,shijian[0:4]) sheet.write(count,1,shijian[5:]) sheet.write(count,2,text2(new_img)) sheet.write(count,3,text3(new_img)) sheet.write(count,4,text4(new_img)) sheet.write(count,5,text5(new_img)) sheet.write(count,6,text6(new_img)) count = count + 1
from wand.image import Image from PIL import Image as PI import pyocr import io import re import os import shutil import pyocr.builders from cnocr import CnOcr import requests import xlrd import xlwt from openpyxl import load_workbook def chineseNumber2Int(strNum: str): result = 0 temp = 1 # 存放一个单位的数字如:十万 count = 0 # 判断是否有chArr cnArr = ['壹', '贰', '叁', '肆', '伍', '陆', '柒', '捌', '玖'] chArr = ['拾', '佰', '仟', '万', '亿'] for i in range(len(strNum)): b = True c = strNum[i] for j in range(len(cnArr)): if c == cnArr[j]: if count != 0: result += temp count = 0 temp = j + 1 b = False break if b: for j in range(len(chArr)): if c == chArr[j]: if j == 0: temp *= 10 elif j == 1: temp *= 100 elif j == 2: temp *= 1000 elif j == 3: temp *= 10000 elif j == 4: temp *= 100000000 count += 1 if i == len(strNum) - 1: result += temp return result def text1(new_img): #提取出票日期 left = 80 top = 143 right = 162 bottom = 162 image_text1 = new_img.crop((left, top, right, bottom)) #展示图片 #image_text1.show() txt1 = tool.image_to_string(image_text1) print(txt1) return str(txt1) def text2(new_img): #提取金额 left = 224 top = 355 right = 585 bottom = 380 image_text2 = new_img.crop((left, top, right, bottom)) #展示图片 #image_text2.show() image_text2.save("img/tmp.png") temp = ocr.ocr("img/tmp.png") temp="".join(temp[0]) txt2=chineseNumber2Int(temp) print(txt2) return txt2 def text3(new_img): #提取出票人 left = 177 top = 207 right = 506 bottom = 231 image_text3 = new_img.crop((left, top, right, bottom)) #展示图片 #image_text3.show() image_text3.save("img/tmp.png") temp = ocr.ocr("img/tmp.png") txt3="".join(temp[0]) print(txt3) return txt3 def text4(new_img): #提取付款行 left = 177 top = 274 right = 492 bottom = 311 image_text4 = new_img.crop((left, top, right, bottom)) #展示图片 #image_text4.show() image_text4.save("img/tmp.png") temp = ocr.ocr("img/tmp.png") txt4="".join(temp[0]) print(txt4) return txt4 def text5(new_img): #提取汇票到日期 left = 92 top = 166 right = 176 bottom = 184 image_text5 = new_img.crop((left, top, right, bottom)) #展示图片 #image_text5.show() txt5 = tool.image_to_string(image_text5) print(txt5) return txt5 def text6(new_img): #提取票据号码 left = 598 top = 166 right = 870 bottom = 182 image_text6 = new_img.crop((left, top, right, bottom)) #展示图片 #image_text6.show() txt6 = tool.image_to_string(image_text6) print(txt6) return txt6 ocr=CnOcr() tool = pyocr.get_available_tools()[0] filePath='img' img_name=[] for i,j,name in os.walk(filePath): img_name=name count=1 book = xlwt.Workbook(encoding='utf-8',style_compression=0) sheet = book.add_sheet('test',cell_overwrite_ok=True) for i in img_name: img_url = filePath+"/"+i with open(img_url, 'rb') as f: a = f.read() new_img = PI.open(io.BytesIO(a)) ## 写入csv col = ('年份','出票日期','金额','出票人','付款行全称','汇票到日期','备注') for j in range(0,7): sheet.write(0,j,col[j]) book.save('1.csv') shijian=text1(new_img) sheet.write(count,0,shijian[0:4]) sheet.write(count,1,shijian[5:]) sheet.write(count,2,text2(new_img)) sheet.write(count,3,text3(new_img)) sheet.write(count,4,text4(new_img)) sheet.write(count,5,text5(new_img)) sheet.write(count,6,text6(new_img)) count = count + 1
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