Overview

OCRmyPDF uses Tesseract to recognize text in PDF page images and embed a searchable text layer. PDF is its supported input, so it is a focused fit for scanned-document workflows rather than a general-purpose OCR tool for arbitrary image files.

PDF/A-2b is the default output, which makes the tool a natural fit for archival workflows; regular PDF output is also an option. Deskew and other image-processing options can improve alignment and OCR conditions, but they cannot compensate for every poor scan. Recognition may lag commercial solutions, and handwriting is not recognized.

Key features

Existing-text controls: The processing modes can error on pages that already contain text, skip them, redo OCR, or force OCR across every page. This gives teams a way to choose how mixed or previously processed documents are handled rather than applying one policy blindly.
Python library and plugins: Python use and processing-step plugins make OCRmyPDF adaptable to custom pipelines. That flexibility is most useful to teams willing to integrate and maintain their own workflow.
Configurable runtime: Tesseract has a default limit of three minutes per page, and images above a configured megapixel threshold can be skipped. These controls help bound processing, but teams handling unusually complex or high-resolution scans should account for pages that may time out or be skipped.
Mixed-language collections therefore need deliberate language configuration.

Pricing

OCRmyPDF costs 0.00 USD per free. The free software is installed and run by the user and depends on external OCR and PDF tools; there is no free trial because the software itself is free. This is a strong fit for teams able to manage their own deployment and dependencies, but not for buyers seeking a packaged hosted service with managed operations.

Commercial use requires compliance with OCRmyPDF’s and its dependencies’ licenses. Ghostscript is required in some workflows and is licensed under AGPLv3, a consideration for teams assessing distribution and deployment obligations.

Platforms

OCRmyPDF supports Linux, macOS, and Windows, as well as self-hosted use and an API designation. Installation methods are documented for Linux, macOS, Windows, FreeBSD, and Docker. The project also identifies Paperless-ngx and Nextcloud OCR as third-party integrations, which can make it relevant to teams building document-management workflows around those tools.

Security needs careful handling: the project advises processing only PDFs users trust. Its example Docker web service has no security measures and is not intended for public internet deployment, so it should not be treated as a ready-made public OCR endpoint.

Who it's for

Choose OCRmyPDF when searchable PDFs are the goal, self-hosting is acceptable, and a team can tune language settings, manage dependencies, and decide how existing text should be treated. Its PDF/A default also suits archival use. Look elsewhere if handwriting recognition, broader input formats, commercial-grade recognition, or a managed online service is central to the requirement.

Pros and cons

Pros

No software charge: The free self-hosted plan avoids a per-seat or usage price for teams that can operate the tool themselves.
Archival output by default: PDF/A-2b is the standard output, with regular PDF available when archival formatting is not wanted.
Workflow flexibility: Existing-text modes, Python use, and plugins support integration into varied processing pipelines.
Deployment choice: Linux, macOS, Windows, Docker, and FreeBSD installation paths give operators multiple ways to run it.

Cons

Recognition has clear limits: Handwriting is unsupported, poor scans can yield poor results, and accuracy may trail commercial solutions.
Language setup matters: Unspecified document languages can lead to poor results, especially in collections with varied language content.
Operators own deployment and safety: External tools are dependencies, and the example web service is explicitly unsuitable for public internet deployment without security measures.

Alternatives

OCR software and OCR API Software are category starting points for comparing broader options.

FreeOCR.AI is worth considering when API, web, or desktop platform availability and paid monthly or annual credit plans fit better than self-hosting; its monthly Pro plan is 10.00 USD per month for 10,000 credits per month, while its yearly Pro plan is 80.00 USD per year for 120,000 credits.
OnlineOCR may suit a web-oriented workflow that needs defined weekly page capacity and file-size limits: its Weekly Plan is 9.95 USD per month with 2,000 pages per week, seven-day validity, and a 200 MB maximum file size; its Monthly Plan is 29.95 USD per month.
PaddleOCR is an alternative to consider for Android or iOS platform needs; its Official API Free Tier has a daily parsing limit of 20,000 pages.
Tesseract OCR is another free option for Linux, Windows, macOS, or Android when choosing the OCR engine itself is preferable.
i2OCR may fit a web-based, one-page-at-a-time workflow.
ABBYY FineReader PDF is a paid alternative for iOS, macOS, or Windows users.
ABBYY Screenshot Reader is a Windows option with a perpetual license at 9.99 USD per once.
Scribe OCR is another free, open-source option with self-hosted and web platforms.

Verdict

OCRmyPDF is a strong choice for technically capable teams that need free, configurable OCR for scanned PDFs and want to keep processing self-hosted. Its archival default, existing-text controls, and Python and plugin support make it especially useful in document pipelines. Choose another tool if handwriting, consistently stronger recognition, or a secured managed web service is a must.

	OCRmyPDF	Tesseract OCR
Free plan	Yes	Yes
Free trial	No	No
Paid from	Free	Free
Open source	No	No
Platforms	api, Linux, macOS, self-hosted, Windows	Android, api, iOS, Linux, macOS, self-hosted, Windows
Free plan	Yes	Yes
Handwriting OCR	No	—
Structure extraction	—	Yes
SDK languages	—	C, C++

OCRmyPDF vs Tesseract OCR

OCRmyPDF

Tesseract OCR