QuickCapture Mobile Scanning SDK Specially designed for native ANDROID from Extrieve
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Updated
Jun 17, 2024 - Kotlin
QuickCapture Mobile Scanning SDK Specially designed for native ANDROID from Extrieve
A hands-on CLI tool sample showcasing the integration of Dart with Google Cloud's DocumentAI.
Official release of RFUND introduced in the paper "PEneo: Unifying Line Extraction, Line Grouping, and Entity Linking for End-to-end Document Pair Extraction" (arXiv:2401.03472).
This small module connects Label Studio with Fonduer by creating a fonduer labeling function for gold labels from a label studio export. Documentation: https://irgroup.github.io/labelstudio-to-fonduer/
QuickCapture Mobile Scanning SDK Specially designed for native IOS
LAISA (Local AI Search Application) is a desktop app which allows you to run completely local, private, and free LLM inference. LAISA supports basic RAG with pre-configured OpenSearch Databases, and local document parsing with PDFs.
(WIP) ✨ A comprehensive resource for understanding the world of software used in the Document Understanding field. 🧙✨
Implementation of the paper: Going Full-TILT Boogie on Document Understanding with Text-Image-Layout Transformer.
Run optical character recognition with PyTesseract from the FiftyOne App!
TAT-DQA: Towards Complex Document Understanding By Discrete Reasoning
This project tackles a real-world challenge of automating client document processing, with a focus on enhancing document classification, error detection, data extraction, and validation.
Datasets and Evaluation Scripts for CompHRDoc
Algorithms, papers, datasets, performance comparisons for Document AI. Continuously updating.
Checkbox Detection Model for Scanned Documents
ReadingBank: A Benchmark Dataset for Reading Order Detection
Object Detection Model for Scanned Documents
A Curated List of Awesome Table Structure Recognition (TSR) Research. Including models, papers, datasets and codes. Continuously updating.
Minimal sharded dataset loaders, decoders, and utils for multi-modal document, image, and text datasets.
Doc2Graph transforms documents into graphs and exploit a GNN to solve several tasks.
Add a description, image, and links to the document-understanding topic page so that developers can more easily learn about it.
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