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PROJECT
Extract Text from PDFs and Images Using Tesseract
In this project, we’ll learn how to create a web-based application for text extraction using basic HTML and CSS for the frontend and Django for the backend. This project uses Tesseract, an open-source OCR engine, to extract text data from PDFs and images.
You will learn to:
Create a text extractor using Django.
Extract text from images.
Extract text from PDFs.
Upload and process dynamically added files.
Skills
Web Development
Django basics
Prerequisites
Basic knowledge of Django and its templates
Basic knowledge of Optical Character Recognition (OCR)
Basic knowledge of CSS and Bootstrap
Technologies
Python
Django
Project Description
Django is an open-source Python framework for creating the backend of web applications. It enables the rapid development of secure and maintainable websites without much hassle. Pytesseract is an Optical Character Recognition (OCR) tool in Python that recognizes and detects hand-written and digitally printed text embedded in images.
In this project, we’ll use Django to create a web-based application for text extraction. We’ll use basic HTML and Bootstrap to create the application’s frontend and styling. The application will allow users to upload their images or PDF files and save them at specified location. Furthermore, we’ll use Tesseract, an open-source OCR engine, to extract text data from PDFs and images.
The basic layout of the application will be as follows:
Project Tasks
1
Get Started
Task 0: Introduction
Task 1: Create and Configure the App
2
Create the Front-end
Task 2: Create a Base View
Task 3: Create a File View
3
Create the Backend
Task 4: Create a File Handler
Task 5: Create a Text Extractor for Images
Task 6: Create a Text Extractor for PDF Files
Task 7: Create a File Checker
Task 8: Create a Function to Upload Files
4
Access the Application
Task 9: Update the File View
Task 10: Creating a Controller
Congratulations!