TrulyFreeOCR – a Java OCR pipeline in a single fat JAR, zero native deps required

Introduction I'm the author of TrulyFreeOCR, an open-source OCR pipeline that turns scanned PDFs into searchable, highly-compressed PDFs. Everything is Apache 2.0 / MIT / BSD — no GPL, no AGPL, no proprietary model weights. Why I built it: I needed an OCR pipeline for a document processing system where: Every dependency had to be business-friendly (no GPL/AGPL) Deployment required zero admin rights (no sudo, no brew, no apt-get) MRC compression was needed to hit 5-10x file size reduction vs JPEG-only Everything had to run offline on CPU — no cloud APIs, no GPU I surveyed 20+ existing tools (full comparison in the repo's docs) and none fit all requirements. OCRmyPDF is closest but needs Python + Ghostscript + Tesseract as system deps, and MPL-2.0 requires publishing modifications. The VLM models (DeepSeek-OCR, GLM-OCR, etc.) produce better text extraction but need GPUs and don't output PDFs at all. What it does: Input: any PDF (scanned, born-digital, or mixed) Output: searchable PDF with invisible text layer + MRC compression (JBIG2/CCITT foreground + JPEG background) Single fat JAR — one file to copy, one command to run Bootstrap script downloads everything (JDK, Gradle, Tesseract, Leptonica, jbig2enc) into project subdirs Fully offline, CPU-only PDF/A-2b output available 7 bundled language models, 100+ more downloadable Concurrent OCR (configurable thread pool) Try it in 3 commands: $ git clone https://github.com/msmarkgu/TrulyFreeOCR.git $ cd TrulyFreeOCR $ ./bootstrap.sh ./run.sh tests/simple-text.pdf -o output.pdf Limitations (being upfront): Tesseract-based accuracy — good for clean scans, not SOTA for noisy/photographed docs No table/formula extraction yet No handwriting recognition CPU-only is slower than GPU backends for high volume Would love feedback — especially from anyone who's tried to deploy OCR in an enterprise environment. https://github.com/msmarkgu/TrulyFreeOCR