OCRmyPDF

What is OCRmyPDF?

OCRmyPDF adds an OCR text layer to scanned PDFs (or images) so they can be searched and copied, and by default writes a PDF/A file for long-term archiving. It uses the Tesseract OCR engine with more than 100 languages, can deskew and rotate pages, optimizes images and spreads work across all CPU cores. It is a command-line program; the Docker image also ships a watcher service that OCRs every PDF dropped into an input folder. Plugins can swap Tesseract for other engines such as EasyOCR or PaddleOCR.

Where it fits in a 10–200 person business

• Make a scanner's output folder searchable by OCRing every new PDF automatically
• Convert archived paper invoices and contracts into searchable PDF/A files
• Add an OCR step to a document pipeline or script before indexing files for RAG

These use cases are our editorial suggestions, not claims made by the project.

Can a business use OCRmyPDF? (license)

This is a plain-English summary of the license text, not legal advice. Third-party models you run with it have their own licenses.

Data & compliance: does OCRmyPDF phone home?

Checked against the project's own docs and repository on Nov 1, 2026. "Not documented" means we could not find the answer in official sources; it does not mean the feature is missing or that no data is sent. Third-party services you connect (model APIs, vector databases, search engines) have their own data policies. Compare all apps.

What hardware does OCRmyPDF need?

The project does not publish a minimum CPU/RAM figure, so we leave the official value blank rather than guess.

GPU: No. Tesseract runs on CPU; the optional EasyOCR plugin is the one that recommends a GPU.

No server minimum is published. The performance page gives a rule of thumb of about 15 bytes per pixel of the largest page per concurrent job: a letter-size page scanned at 600 dpi peaks at roughly 500 MB with --jobs 1 and roughly 2 GB with --jobs 4. For temporary storage, allow about 100 MB per page being processed.

Source: ocrmypdf.readthedocs.io/en/latest/performance.html

How much does it cost to host OCRmyPDF per month?

How to deploy OCRmyPDF

Method: Docker (watched-folder service)

docker run \
    --volume <path to files to convert>:/input \
    --volume <path to store results>:/output \
    --volume <path to store processed originals>:/processed \
    --env OCR_OUTPUT_STRUCTURE=YEAR_MONTH \
    --env OCR_ON_SUCCESS_ARCHIVE=1 \
    --env OCR_DESKEW=1 \
    --env PYTHONUNBUFFERED=1 \
    --interactive --tty --entrypoint python3 \
    jbarlow83/ocrmypdf \
    /app/watcher.py
# One-off files: docker run --rm -i jbarlow83/ocrmypdf-alpine - - <input.pdf >output.pdf

From the official instructions: ocrmypdf.readthedocs.io/en/latest/batch.html. Always check the source for the current version before you run it.

Known gotchas when self-hosting OCRmyPDF

• The image runs as the non-root app user (uid 1000), so it may not be able to write to bind-mounted /output and /processed folders unless you pass a --user value that matches rootful Docker, rootless Docker or Podman. source
• The bundled web service (webservice.py) is for demonstration only: it has no authentication, no security and no protection against denial of service. Do not expose it to users. source
• OCRmyPDF is not designed to process PDFs uploaded by untrusted users, and it uses all CPU cores and a lot of temporary disk by default. Limit --jobs or the container's resources on a shared server. source
• The Docker image includes only English, German, Simplified Chinese, French, Portuguese and Spanish. Other languages need a custom image built on top of the official one. source

Alternatives in Document processing

• PaddleOCR OCR toolkit and document AI engine that turns scans, images and PDFs into LLM-ready text, Markdown or JSON. Compare OCRmyPDF vs PaddleOCR
• MinerU Document parser that converts PDFs, scans and Office files into clean Markdown or JSON for LLMs and RAG. Compare MinerU vs OCRmyPDF
• Paperless-ngx Document management system that OCRs scans into a searchable archive, auto-tags them and adds optional LLM suggestions and chat. Compare OCRmyPDF vs Paperless-ngx
• Unstract No-code LLM platform that turns invoices, forms and other documents into structured JSON. Compare OCRmyPDF vs Unstract
• Paperless-AI AI auto-tagging and document chat for Paperless-ngx (currently unmaintained). Compare OCRmyPDF vs Paperless-AI
• paperless-gpt LLM add-on for paperless-ngx that does better OCR and writes titles, tags and correspondents. Compare OCRmyPDF vs paperless-gpt
• Docling Serve Docling document conversion (PDF, Office, images to Markdown/JSON) as a self-hosted API with a demo UI. Compare Docling Serve vs OCRmyPDF

Sources

• GitHub repository: github.com/ocrmypdf/OCRmyPDF
• Official documentation: ocrmypdf.readthedocs.io/en/latest/
• License text: github.com/ocrmypdf/OCRmyPDF/blob/main/LICENSE
• Hardware requirements: ocrmypdf.readthedocs.io/en/latest/performance.html
• Deploy instructions, Gotcha 1: ocrmypdf.readthedocs.io/en/latest/batch.html
• Gotcha 2, Gotcha 4: ocrmypdf.readthedocs.io/en/latest/docker.html
• Gotcha 3: ocrmypdf.readthedocs.io/en/latest/cloud.html
• Hetzner Cloud pricing (cost estimate): www.hetzner.com/cloud/regular-performance
• GitHub stars, commits and releases: GitHub REST API, fetched Nov 1, 2026