I want to extract dates from OCR images using the dateparser
lib.
import dateparser
data = []
listOfPages = glob.glob(r"C:/Users/name/folder/test/*.tif")
for entry in listOfPages:
text1 = pytesseract.image_to_string(
Image.open(entry), lang="deu"
)
text = re.sub(r'\n',' ', text1)
date1 = re.compile(r'(Dresden(\.|,|\s+)?)(.*)', flags = re.DOTALL | re.MULTILINE)
date = date1.search(text)
if date:
dates = dateparser.parse(date.group(3), date_formats=['%d %m %Y'], languages=['de'], settings={'STRICT_PARSING': True})
else:
dates = None
if dates == None:
dates = dateparser.parse(date.group(3), date_formats=['%d %B %Y'], locale = 'de', settings={'STRICT_PARSING': True})
else:
dates = None
data.append([text, dates])
df0 = pd.DataFrame(data, columns =['raw_text', 'dates'])
print(df0)
Why am i getting error: NameError: name 'dates' is not defined
update: TypeError: Input type must be str
The problem is that your date
is a match data object. Also, I am not sure dateparser.parse
does what you need. I'd recommend datefinder
package to extract dates from text.
This is the regex I'd use:
\bDresden(?:[.,]|\s+)?(.*)
See the regex demo. It matches Dresden
as a whole word (\b
is a word boundary), (?:[.,]|\s+)?
is a non-capturing optional group matching ,
, .
or one or more whitespaces, and then captures into Group 1 any zero or more chars (re.DOTALL
allows .
to match line separators, too).
Here is the Python snippet that seems to yield expected matches:
import pytesseract, dateparser, glob, re
import pandas as pd
import datefinder
from pytesseract.pytesseract import Image
imgpath = r'1.tif'
data = []
listOfPages = glob.glob(r"C:/Users/name/folder/test/*.tif")
listOfPages = [imgpath]
for entry in listOfPages:
text = pytesseract.image_to_string(
Image.open(entry), lang="deu"
)
dates = []
date = re.search(r'\bDresden(?:[.,]|\s+)?(.*)', text, re.DOTALL)
if date:
dates = [t.strftime("%d %B %Y") for t in datefinder.find_dates(date.group(1))]
#dates = dateparser.parse(date.group(1), date_formats=['%d %m %Y'], languages=['de'], settings={'STRICT_PARSING': True})
data.append([text, dates])
df0 = pd.DataFrame(data, columns =['raw_text', 'dates'])
print(df0)
With your sample image, I get
raw_text dates
0 Sächsischer Landtag DRUCKSACHE , 1972\n2. Wahl... [17 October 1995, 18 October 1995]