general OCR / document parsing
OpenOCR is an open-source toolkit for general OCR and document parsing, integrating training/evaluation benchmarks, commercial-grade OCR, and reproductions of academic implementations.
Same problem, same approach. Swapping one for another is a config change, not a rewrite.
Full-featured OCR toolkit with broad language support and pretrained models, a mature drop-in peer for OpenOCR.
Turn any PDF or image document into structured data for your AI. A powerful, lightweight OCR toolkit that bridges the gap between images/PDFs and LLMs. Supports 100+ languages.
Comprehensive PDF content extraction with text, formula, and table recognition, a strong peer to OpenOCR for document parsing.
A Comprehensive Toolkit for High-Quality PDF Content Extraction
Deep learning OCR library for detection and recognition, easy to integrate, comparable to OpenOCR.
docTR (Document Text Recognition) - a seamless, high-performing & accessible library for OCR-related tasks powered by Deep Learning. Ongoing development and maintenance by t2k.
Ready-to-use OCR with 80+ languages, simple API, a lightweight drop-in alternative to OpenOCR.
Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc.
Solves the same problem with a different architecture or at a different layer. Expect to rewrite the integration.
A transformer-based OCR model with a different architecture, suitable when you want a single powerful model rather than a full toolkit.
GLM-OCR: Accurate × Fast × Comprehensive
OCR-free document extraction and markdown conversion, a different approach from traditional OCR pipelines.
An on-premises, OCR-free unstructured data extraction, markdown conversion and benchmarking toolkit. (https://idp-leaderboard.org/)
An earlier or more limited way to do the job. Still the right call when you need something small, proven, or CPU-only.
Research code collection from Alibaba's OCR team, not a unified toolkit, useful for reproducing specific papers rather than as a drop-in library.
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.
Specialized in table extraction only, choose when you need just that subtask and want a lightweight toolkit.
A Unified Toolkit for Deep Learning-Based Table Extraction
Focused on document layout analysis rather than full OCR/parsing, useful for region detection tasks.
A Unified Toolkit for Deep Learning Based Document Image Analysis
Older pure-PyTorch OCR with text detection and recognition, simpler but less comprehensive than OpenOCR.
A pure pytorch implemented ocr project including text detection and recognition
Parses text-layer documents in Rust, no image OCR support; choose for digital PDFs only.
A fast, helpful, and open-source document parser
Focuses on text recognition only, with benchmark code; not a complete OCR/detection toolkit.
Text recognition (optical character recognition) with deep learning methods, ICCV 2019
Dedicated to curve text detection, a narrower subproblem than general OCR.
This repository provides train＆test code, dataset, det.&rec. annotation, evaluation script, annotation tool, and ranking.
Specialized for high-resolution Urdu text recognition, very narrow scope.
UTRNet: High-Resolution Urdu Text Recognition In Printed Documents (ICDAR'23)
A single document image parsing model from a paper, not a full toolkit, narrower than OpenOCR.
The official repo for “Dolphin: Document Image Parsing via Heterogeneous Anchor Prompting”, ACL, 2025.
Legacy Chinese scene-text OCR with CTPN/CRNN, older and less general than OpenOCR.
End-to-end Chinese scene-text detection and recognition with CTPN, CRNN, and CTC (legacy project).
Does the same job, but ships as an app. Useful to a person, not swappable into a codebase.
Python SDK for a cloud document parsing service, not a self-hosted library.
Python SDK for OCR and document parsing in the cloud with LlamaParse
A document parsing AI tool with a Vue-based UI, not a library for embedding in code.
With DocSlight, precisely parse and extract data from any document, including PDFs, scans, images, and Office files. It is an open-source AI project from ComPDF (KDAN ecosystem).
Duplicate/fork of the ComPDF doc parsing app, end-user tool rather than a code library.
Part of the KDAN ecosystem, DocSlight offers document parsing, OCR, and data extraction that turn PDFs, scans, images, and Office files into structured outputs for RAG pipelines, AI agents, and enterprise document automation.
These projects were analysed and named OpenOCR among their alternatives. The relationship is not symmetric — how OpenOCR rates them is a separate judgement, made when OpenOCR is analysed in its own right.
calls OpenOCR “if you want an open-source toolkit with unified training/evaluation and reproducible OCR baselines.”
Turn any PDF or image document into structured data for your AI. A powerful, lightweight OCR toolkit that bridges the gap between images/PDFs and LLMs. Supports 100+ languages.