OCRmyPDF vs PaddleOCR

OCRmyPDF is free software that adds searchable text to scanned PDF files while retaining the original PDF as much as possible. It uses Tesseract to recognize text in page images and produces PDF/A-2b by default, with regular PDF output available as an alternative. Image-processing options such as deskew can adjust pages to support visual quality and OCR accuracy. When a PDF already contains text, its processing modes can stop with an error, skip affected pages, redo OCR, or force OCR across all pages. OCRmyPDF can also be used as a Python library, and plugins can customize processing steps. Installation methods are documented for Linux, macOS, Windows, FreeBSD, and Docker; Paperless-ngx and Nextcloud OCR are named as third-party integrations. Results may be poor for low-quality scans or languages not specified for processing, and handwriting is not recognized. The project also notes that accuracy may trail commercial solutions. Its documentation advises processing only PDFs users trust and warns that its example Docker web service has no security measures and is not meant for public internet deployment.

PaddleOCR is an open-source OCR and document-processing toolkit for extracting text and structure from documents. Its PP-StructureV3 component turns complex PDFs and document images into Markdown and JSON while preserving their organization, and supports table extraction. PaddleOCR-VL handles multilingual document parsing across 109 languages, while PP-OCRv6 supports 50 languages in one model. PaddleOCR 3.0 also recognizes handwriting. For large document collections, PP-ChatOCRv4 extracts key information and integrates ERNIE 4.5. Models can be used online through the official website or called through an API; the official free API allows up to 20,000 pages of document parsing per day. Documentation describes local, C++, service, Android, iOS, and browser deployment options, among others. The license permits use, modification, distribution, and sale without restriction. SDK languages listed are Python, TypeScript, and Go. Support is available through GitHub Issues. One compatibility note: code written for PaddleOCR 2.x may not run with version 3.x.