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In today's fast-paced business environment, efficiently managing and organizing contact information is crucial for successful networking and communication. With the advent of digital tools and technologies, manual entry of business card details into a database can be time-consuming and prone to errors. To overcome these challenges, developers can leverage the power of optical character recognition (OCR) and databases to automate the process of extracting relevant information from business cards and storing it for easy access.
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One powerful OCR library that facilitates the extraction of text from images is EasyOCR. EasyOCR is an open-source Python library that utilizes deep learning models to accurately recognize and extract text from various languages. By integrating EasyOCR with a MySQL database, developers can streamline the process of capturing business card data and storing it in a structured and organized manner.
- Virtual code.
- Jupyter notebook.
- Python 3.11.0 or higher.
- MySQL.
- pip install pandas easyocr numpy Pillow opencv-python-headless os re sqlalchemy mysql-connector-python streamlit
- import easyocr # (Optical Character Recognition)
- import numpy as np
- from PIL
- from PIL import Image, ImageDraw
- import cv2
- import os
- import re
- import pandas as pd
- import sqlalchemy
- import mysql.connector
- from sqlalchemy import create_engine, inspect
- import streamlit as st
- Extract relevant information from business cards by using the easyOCR library
- After the extraction process, process the extracted data based on Company name, Card Holder, Designation, Mobile Number, Email, Website, Area, City, State, and Pincode is converted into a data frame.
- After the transformation process, the data is stored in the MySQL database.
- Click the 'Browse Files' button and select an image
- Click the 'Upload to MySQL DB' button to upload the data to the Mysql database
- In this 'Modification zone' you can able to modify the information also you can delete the previous data