Recognize dates from an image using Sliding Window Algorithm & Python OCR.

In this article, we’ll see how to recognize dates of different formats from any image of a document using Python.

Hey there 👋, Today let’s solve a text processing problem that asks us to find any “date” present in a string.

We are using “easyocr”, a python OCR library to find the text from the images. Let’s move on with the code.

Extracting text from images | Setting up easyocr

1. We start by creating a data-extraction.py module.
2. 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, we’ll consider only a few well-known forms.

We’ll try to identify “dd mmm yyyy” date formats from a string.

For example, if the given date is “15 sd f may 2019”, then the output should be “15–05–2019".

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 “𝗴𝘀 𝟭𝟱 𝗺𝗮𝗶 𝗺𝗮𝘆 𝟮𝟬𝟭𝟵 𝘀𝗴𝗳 𝘀”. The date should be 15th May 2019.

Showing sliding window in progress

1. The first step is to implement a sliding window to convert “MMM” to a number. Like, may to 05.
2. 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 = "𝗴𝘀 𝟭𝟱 𝗺𝗮𝗶 𝗺𝗮𝘆 𝟮𝟬𝟭𝟵 𝘀𝗴𝗳 "
        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. That’s 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 “date” 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 “date” 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)

That’s all folks!

We’ll meet on my next blog. Till then, take care!

Happy Coding 🤟