Скачать или смотреть DocTagger: Efficient Data Extraction and Tagging from PDF Documents

Welcome to our DocTagger project demo! This video showcases an advanced tool designed for efficient data extraction and tagging from PDF documents. Whether you're a researcher, data analyst, or just need to manage information from PDFs, this Python-based application has you covered.

Features:

• Easy PDF Upload: Quickly upload PDF files for processing.
• Data Extraction: Extract text and metadata using PyMuPDF (fitz).
• Custom Tagging: Apply and manage tags for organized data.
• Reset Functionality: Easily start fresh with new PDFs.

Why DocTagger?
Our tool leverages Python's powerful libraries and a user-friendly GUI built with tkinter and ttkbootstrap. This combination provides a seamless experience for users needing to extract and categorize data from PDF files.

🔗 Download the Code & Get Started: https://github.com/iAveshh/DocTagger

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