Recognize dates from an image using Sliding Window Algorithm & Python OCR.
In this article, weโll see how to recognize dates of different formats from any image of a document using Python.
Hey there ๐, Today letโs solve a text processing problem that asks us to find any โdateโ present in a string.
We are using โeasyocrโ, a python OCR library to find the text from the images. Letโs move on with the code.
Extracting text from images | Setting up easyocr
- We start by creating a data-extraction.py module.
- Install easyocr library.
$ pip install easyocr
3. Create a DataExtraction class and initiate the easyocr model.
# data-extraction.py
from datetime import datetime
import easyocr
import re
class DataExtraction:
def __init__(self) -> None:
self.months = {
"JAN": "01",
"FEB": "02",
"MAR": "03",
"APR": "04",
"MAY": "05",
"JUN": "06",
"JUL": "07",
"AUG": "08",
"SEP": "09",
"OCT": "10",
"NOV": "11",
"DEC": "12",
}
self.reader = easyocr.Reader(["en"])
4. Easyocr gives us a list of strings obtained from the image.
Converting date strings to DateTime objects
There can be an unknown number of date formats and parsing each one of them will take an infinite amount of time and work. So in this example, weโll consider only a few well-known forms.
Weโll try to identify โdd mmm yyyyโ date formats from a string.
For example, if the given date is โ15 sd f may 2019โ, then the output should be โ15โ05โ2019".
We are going to use the Sliding Window to detect if any month is present in between two groups of numerical characters.
The string includes numbers, alphabets, including other characters. For example, consider โ๐ด๐ ๐ญ๐ฑ ๐บ๐ฎ๐ถ ๐บ๐ฎ๐ ๐ฎ๐ฌ๐ญ๐ต ๐๐ด๐ณ ๐โ. The date should be 15th May 2019.
- The first step is to implement a sliding window to convert โMMMโ to a number. Like, may to 05.
- We create a function that takes in a string and finds if it contains any month from the above dictionary, months.
# Sliding Window implementation
def month_to_num(self, s: str) -> str:
res = ""
start = 0
try:
for end in range(len(s)):
rightChar = s[end]
res += rightChar
if len(res) == 3:
if res.upper() in self.months.keys():
numeric_date = self.months[res.upper()]
return numeric_date
start += 1
res = res[1:]
except Exception as e:
pass
return ""
3. Next, we create a function that takes in a string and gives us the desired format.
def find_date_string(self, s: str) -> list: # s = "๐ด๐ ๐ญ๐ฑ ๐บ๐ฎ๐ถ ๐บ๐ฎ๐ ๐ฎ๐ฌ๐ญ๐ต ๐๐ด๐ณ "
s1 = " ".join(re.split(r"([a-zA-Z])([0-9]+)", s))
s2 = " ".join(re.split(r"([0-9]+)([a-zA-Z]+)", s1))
text = "-" + "-".join(re.split(r"[-;,.\s]\s*", s2)) + "-" # "gs-15-mai-may-2019-sgf"
dates_type_1 = re.findall(r"-[0-9][0-9]-.*?-[0-9][0-9][0-9][0-9]-", text) # "-15-mai-may-2019"
date_objects = []
# in-case there is a desired date formats
if len(dates_type_1) > 0:
date_objs = self.get_date_object(dates_type_1)
for date_obj in date_objs:
date_objects.append(date_obj)
return date_objects
def get_date_object(self, date_type_1_list: list):
dates = []
# there might be more than one date in a single string.
for date_str in date_type_1_list:
day_str = date_str[1:3]
month_str = date_str[3:-4]
year_str = date_str[-5:-1]
month_number = self.month_to_num(month_str)
if month_number == "":
return ""
result_date_str = f"{day_str}-{month_number}-{year_str}"
date_object = datetime.strptime(result_date_str, "%d-%m-%Y")
dates.append(date_object)
return dates
4. Now we just need to pass the extracted strings into the above functions.
def get_date_from_img(self, img_path: str):
result = []
# extract the texts from the img
text_strings = self.reader.readtext(img_path, detail=0)
# check every string for dates
for s in text_strings:
date_obj_list = self.find_date_string(s)
if len(date_obj_list) > 0:
result.append(date_obj_list)
return result
5. Thatโs it. We have all the DateTime objects present in a document image.
This method can be used on any kind of document, provided the date format matches the defined type. There are many kinds of โdateโ formats used throughout the world. Different countries have different formats. Parsing each one of them will require some more effort but it is definitely achievable.
Here are some of the other formats to be used for different โdateโ types.
"""
1. 1 mai/may 2019
2. 1 mai/may 19
3. 12 09 2016
4. 2 09 2016
5. 12 09 16
6. 2 09 16
"""
dates_type_2 = re.findall(r"-[0-9][0-9]-[0-9][0-9]-[0-9][0-9][0-9][0-9]-", text)
dates_type_3 = re.findall(r"-[0-9][0-9]-[0-9][0-9]-[0-9][0-9]-", text)
dates_type_4 = re.findall(r"-[0-9][0-9]-.*?-[0-9][0-9]-", text)
dates_type_5 = re.findall(r"-[0-9]-.*?-[0-9][0-9]-", text)
dates_type_6 = re.findall(r"-[0-9]-.*?-[0-9][0-9][0-9][0-9]-", text)
dates_type_7 = re.findall(r"-[0-9]-[0-9][0-9]-[0-9][0-9]-", text)
dates_type_8 = re.findall(r"-[0-9]-[0-9][0-9]-[0-9][0-9][0-9][0-9]-", text)
Thatโs all folks!
Weโll meet on my next blog. Till then, take care!
Happy Coding ๐ค