Python tool for converting files and office documents to Markdown. - microsoft/markitdown

A powerful, privacy-first PDF editor that runs in your browser or locally on your computer. Add text, signatures, merge, split, export to DOCX — 39 features, completely free and offline. Files never touch our servers.

via: https://news.ycombinator.com/item?id=46924075

As the title says, a cookbook on working with structured data, by people who created open source OCR and document processing tools

OCR Arena is a free playground for testing and evaluating leading foundation VLMs and open source OCR models side-by-side. Upload a document, measure accuracy, and vote for the best models on a public leaderboard.

Datalab’s Chandra topped independent benchmarks and beat the previously best dots-ocr.

• Support for 40+ languages
• Handles text, tables, formulas seamlessly

A toolkit for converting PDFs and other image-based document formats into clean, readable, plain text format.

Try the online demo: https://olmocr.allenai.org/

Features:

Convert PDF, PNG, and JPEG based documents into clean Markdown Support for equations, tables, handwriting, and complex formatting Automatically removes headers and footers Convert into text with a natural reading order, even in the presence of figures, multi-column layouts, and insets Efficient, less than $200 USD per million pages converted (Based on a 7B parameter VLM, so it requires a GPU)

Contexts Optical Compression. Contribute to deepseek-ai/DeepSeek-OCR development by creating an account on GitHub.

An AI Model Just Compressed An Entire Encyclopedia Into A Single, High-Resolution Image.

This article will cover the top ten OCR libraries in Python, highlighting their strengths, unique features, and code examples to help you get started.

OCR-powered screenshot tool to capture text instead of images.

Open Source Document Management System for Digital Archives (Scanned Documents) - papermerge/docker-compose.yml at master · ciur/papermerge

Frustrated by the limitations of Tesseract OCR to extract text from meme images, the author found a way to leverage the iOS Vision API capabilities from older iphones models connected to a Raspberry Pi to build his own OCR service.