A one-stop, open-source, high-quality data extraction tool, supports PDF/webpage/e-book extraction.一站式开源高质量数据提取工具，支持PDF/网页/多格式电子书提取。

Read and extract text and other content from PDFs in C# (port of PDFBox)

A collection of original, innovative ideas and algorithms towards Advanced Literate Machinery. This project is maintained by the OCR Team in the Language Technology Lab, Tongyi Lab, Alibaba Group.

A curated list of resources for Document Understanding (DU) topic

This repository provides train＆test code, dataset, det.&rec. annotation, evaluation script, annotation tool, and ranking.

Code for the paper "PICK: Processing Key Information Extraction from Documents using Improved Graph Learning-Convolutional Networks" (ICPR 2020)

Official PyTorch implementation of LiLT: A Simple yet Effective Language-Independent Layout Transformer for Structured Document Understanding (ACL 2022)

Pandora is an analysis framework to discover if a file is suspicious and conveniently show the results

AssemblyLine 4: File triage and malware analysis

A package for parsing PDFs and analyzing their content using LLMs.

Dedoc is a library (service) for automate documents parsing and bringing to a uniform format. It automatically extracts content, logical structure, tables, and meta information from textual electronic documents. (Parse document; Document content extraction; Logical structure extraction; PDF parser; Scanned document parser; DOCX parser; HTML parser

RObust document image BINarization

Local adaptive image binarization

Document Visual Question Answering

Powerful web application that combines Streamlit, LangChain, and Pinecone to simplify document analysis. Powered by OpenAI's GPT-3, RAG enables dynamic, interactive document conversations, making it ideal for efficient document retrieval and summarization.

Post-process Amazon Textract results with Hugging Face transformer models for document understanding

(ICFHR 2020 oral) Code for "docExtractor: An off-the-shelf historical document element extraction" paper

Effortlessly extract information from unstructured data with this library, utilizing advanced AI techniques. Compose AI in customizable pipelines and diverse sources for your projects.

YOLO models trained by DocLayNet - power your Document Intelligent by Layout Analysis

An unofficial PyTorch implementation of "Lin et al. ViBERTgrid: A Jointly Trained Multi-Modal 2D Document Representation for Key Information Extraction from Documents. ICDAR, 2021"