#Table-extraction
Showing 12 of 12 repositories tagged #table-extraction, ranked by stars
Plumb a PDF for detailed information about each char, rectangle, line, et cetera — and easily extract text and tables.
PyMuPDF is a high performance Python library for data extraction, analysis, conversion & manipulation of PDF (and other) documents.
A polyglot document intelligence framework with a Rust core. Extract text, metadata, images, and structured information from PDFs, Office documents, images, and 97+ formats. Available for Rust, Python, Ruby, Java, Go, PHP, Elixir, C#, R, C, TypeScript (Node/Bun/Wasm/Deno)- or use via CLI, REST API, or MCP server.
An on-premises, OCR-free unstructured data extraction, markdown conversion and benchmarking toolkit. (https://idp-leaderboard.org/)
PDF to markdown using vision LLMs — tables, layouts, and structure preserved
img2table is a table identification and extraction Python Library for PDF and images, based on OpenCV image processing
ParseBench - A Document Parsing Benchmark for AI Agents
Pure Rust PDF library for AI/RAG: structure-aware chunking, no ML, no C deps.
🔍 Table Extraction Tool: A powerful open-source solution combining OCR and computer vision for extracting structured tabular data from images. Ideal for LLM preprocessing, data analysis, and automation. 🚀
Automated data extraction from engineering blueprint images.
An MCP server that lets Claude Code and other AI agents work through large PDFs without overflowing their context — search by meaning or keyword, read only the pages that matter, and cleanly pull out tables, images, and scanned text, even from multi-column and Japanese layouts.
Parse any file in opencode. Supports PDF, DOCX, XLSX, PPTX, images, EPUB, HTML, Markdown, Jupyter, archives, and plain text.