This project focuses on utilizing Optical Character Recognition (OCR) for the extraction of data from business cards. The extracted data is presented in an interactive Streamlit user interface, and efficient data storage is optimized using PostgreSQL.

Optical Character Recognition (OCR) Utilization: Extracts data from business cards using OCR technology.

Interactive User Interface: Presents the extracted data in an interactive Streamlit user interface.

Efficient Data Storage: Optimizes data storage and management using PostgreSQL.

Code Organization: The project includes well-organized code and animation files for efficient development and debugging.

Sample Data Provided: Includes a 'business card image' folder with five sample card images for data extraction.

Visual Representation: Provides GUI screenshots in the 'biscard gui' file for visualization and project understanding.

Ensure the necessary libraries mentioned in the biscard.py file are installed.

The code folder contains all the code and animation files for this project.
The 'bussiness card image' folder includes five sample card images for data extraction.
GUI screenshots of this project are provided in the 'biscard gui' file.

A 'Biscardx' class has been created to handle various project executions, such as text extraction, data storage, data retrieval, data modification, and data deletion processes.

data_x_2_sql: This method encompasses the entire project execution, including text extraction, data storage, data retrieval, data modification, and data deletion processes.

Note: Streamlit is used in this project to present code in a user-friendly UI with captivating animations.

Python (Scripting)
Text Extraction: easyOCR Library
MongoDB
SQL
Data Management using PostgreSQL
User Interface: Streamlit
IDE: PyCharm Community Version