Gopinathalpha7 / BizCardX-Extracting_Business_Card_Data_with_OCR

[ Extract relevant information from business cards by using easyOCR library and stored into MySQL Database ] | Python | easyOCR | MySQL | Streamlit |

BizCardX-Extracting Business Card Data by using easyOCR (Optical Character Recognition)

Introduction

• 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.

• 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.

Developer Guide

1. Tools Install

• Virtual code.
• Jupyter notebook.
• Python 3.11.0 or higher.
• MySQL.

2. Requirement Libraries to Install

• pip install pandas easyocr numpy Pillow opencv-python-headless os re sqlalchemy mysql-connector-python streamlit

3.Import Libraries

Scanning library

• import easyocr # (Optical Character Recognition)
• import numpy as np
• from PIL
• from PIL import Image, ImageDraw
• import cv2
• import os
• import re

Data frame libraries

• import pandas as pd

Database Library

• import sqlalchemy
• import mysql.connector
• from sqlalchemy import create_engine, inspect

Dashboard library

• import streamlit as st

4. E T L Process

a) Extract data

• Extract relevant information from business cards by using the easyOCR library

b) Process and Transform the data

• 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.

c) Load data

• After the transformation process, the data is stored in the MySQL database.

User Guide

Step 1. Data collection zone

• Click the 'Browse Files' button and select an image

Step 2. Data upload

• Click the 'Upload to MySQL DB' button to upload the data to the Mysql database

Step 3. Modification zone

• In this 'Modification zone' you can able to modify the information also you can delete the previous data

Video link

• Click the below Image