OCRmyPDF vs Tesseract OCR

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.

Tesseract OCR is a free, open-source OCR engine and command-line program for extracting printed text from images. It accepts image inputs including PNG, JPEG, and TIFF, and can output plain text, hOCR, PDF, TSV, ALTO, and PAGE formats. PDF options include searchable PDFs and invisible-text-only PDFs. Tesseract 4 and later include an LSTM-based engine focused on line recognition, while Legacy OCR Engine mode retains compatibility with Tesseract 3. The project says it recognizes more than 100 languages out of the box; language data is installed separately from the engine. Developers can build applications with the C or C++ libtesseract API, and the documentation lists wrappers for other languages. The repository code uses the Apache License 2.0. Tesseract does not include a graphical user interface and points users to third-party interfaces. It uses Leptonica to open images, and improving input image quality may be needed for better recognition results. Installation instructions cover Linux, macOS, and Windows, with listed platforms also including Android and self-hosting.