我正在尝试使用计算机视觉从 pdf/图像发票中提取数据。为此，我使用了基于 ocr 的 pytesseract。
这是发票样本
你可以在下面找到相同的代码
import pytesseract
img = Image.open("invoice-sample.jpg")
text = pytesseract.image_to_string(img)
print(text)
http://mrsinvoice.com
’ Invoice
Your Company LLC Address 123, State, My Country P 111-222-333, F 111-222-334
BILLTO:
fofin Oe Invoice # 00001
Alpha Bravo Road 33 Invoice Date 32/12/2001
P: 111-292-333, F: 111-222-334
[email protected] Nomecof Reps Bob
Contact Phone 101-102-103
SHIPPING TO:
eine ce Payment Terms ash on Delivery
Office Road 38
P: 111-333-222, F: 122-222-334 Amount Due: $4,170
[email protected]
NO PRODUCTS / SERVICE QUANTITY / RATE / UNIT AMOUNT
HOURS: PRICE
1 tye 2 $20 $40
2__| Steering Wheel 5 $10 $50
3 | Engine oil 10 $15 $150
4 | Brake Pad 24 $1000 $2,400
Subtotal $275
Tax (10%) $27.5
Grand Total $202.5
‘THANK YOU FOR YOUR BUSINESS
预期产出
{'date': (2014, 6, 4), 'invoice_number': 'EUVINS1-OF5-DE-120725895', 'amount': 35.24, 'desc': 'Invoice EUVINS1-OF5-DE-120725895 from Amazon EU'}
invoice2data python 库，但它也有很多限制。我也尝试了正则表达式和opencv的canny边缘检测来分别检测文本框但未能达到预期的结果你们能帮我吗
最佳答案
您必须进行更多处理，尤其是因为 BILL TO 和 SHIPPING TO 与发票表不一致。但是您可以使用以下代码作为基础。
import cv2
import pytesseract
from pytesseract import Output
import pandas as pd
img = cv2.imread("aF0Dc.jpg")
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
thresh = cv2.threshold(gray, 127, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)[1]
custom_config = r'-l eng --oem 1 --psm 6 '
d = pytesseract.image_to_data(thresh, config=custom_config, output_type=Output.DICT)
df = pd.DataFrame(d)
df1 = df[(df.conf != '-1') & (df.text != ' ') & (df.text != '')]
pd.set_option('display.max_rows', None)
pd.set_option('display.max_columns', None)
sorted_blocks = df1.groupby('block_num').first().sort_values('top').index.tolist()
for block in sorted_blocks:
curr = df1[df1['block_num'] == block]
sel = curr[curr.text.str.len() > 3]
# sel = curr
char_w = (sel.width / sel.text.str.len()).mean()
prev_par, prev_line, prev_left = 0, 0, 0
text = ''
for ix, ln in curr.iterrows():
# add new line when necessary
if prev_par != ln['par_num']:
text += '\n'
prev_par = ln['par_num']
prev_line = ln['line_num']
prev_left = 0
elif prev_line != ln['line_num']:
text += '\n'
prev_line = ln['line_num']
prev_left = 0
added = 0 # num of spaces that should be added
if ln['left'] / char_w > prev_left + 1:
added = int((ln['left']) / char_w) - prev_left
text += ' ' * added
text += ln['text'] + ' '
prev_left += len(ln['text']) + added + 1
text += '\n'
print(text)
结果
bhttps//mrsinvoice.com
Lp
I |
Your Company LLC Address 123, State, My Country P 111-222-333, F 111-222-334
BILL TO:
P: 111-222-333, F: 111-222-334 m .
dlent@ccomplent
Contact Phone 101-102-103
john Doe office ayment Terms ash on Delivery
Office Road 38
P: 111-833-222, F: 122-222-334 Amount Due: $4,170
[email protected]
NO PRODUCTS / SERVICE QUANTITY / RATE / UNIT AMOUNT
HOURS, PRICE
1 | tyre 2 $20 $40
2 | Steering Wheet 5 $10 $50
3 | Engine ol 40 $15 $150
4 | Brake Pad 2a $1000 $2,400
Subtotal $275
Tax (10%) $275
Grand Total $302.5
‘THANK YOU FOR YOUR BUSINESS
关于python-3.x - 如何以表格格式从发票中提取数据，我们在Stack Overflow上找到一个类似的问题：https://stackoverflow.com/questions/61265666/