# nguyenq/tess4j

Java JNA wrapper for Tesseract OCR API

Repository: https://github.com/nguyenq/tess4j
Canonical: https://ross.abutalabs.com/products/tess4j
Language: Java
License: Apache-2.0
License Family: permissive
Last push: 2026-07-28T19:31:22+00:00

## Health v2 (maintenance only)
Score: 91/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 94, release rhythm 83, longevity 100
- inputs: {"age_days": 4452, "days_push": 36, "days_rel": 37, "gap_med": 87.0, "n_releases_24m": 7}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1757, forks 379 (observed 2026-08-28T04:05:32.277340+00:00)

## What it is
Tess4J is a Java JNA wrapper for the Tesseract OCR API, enabling optical character recognition in Java applications. It supports TIFF, JPEG, GIF, PNG, and BMP images, multi-page TIFFs, and PDF documents.

## Use cases
- extract text from scanned images in java
- ocr pdf documents programmatically
- read text from png or jpeg files
- convert multi-page tiff to searchable text
- add ocr capability to a java application
- digitize scanned documents

## When to choose
- you need OCR from Java/JVM code
- you want Tesseract capabilities without shelling out to the CLI
- you need to process images or PDFs for text extraction

## When to avoid
- you need OCR in non-JVM languages (use Tesseract directly)
- you need state-of-the-art accuracy on handwriting or complex layouts
- you want a pure-Java solution without native dependencies

## Facets
- artifact type: library
- maturity: stable
- function: ocr, image-processing, pdf
- domain: computer-vision, image-processing, pdf, developer-tools
- platform: cross-platform, jvm, windows
- tags: tesseract, java, jna, text-extraction, linux, macos

## Member repositories
- nguyenq/tess4j (main) score 91

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:32.277340+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:27:40.142269+00:00, confidence not recorded.
  - readme: https://github.com/nguyenq/tess4j (fetched 2026-08-28T04:05:32.277340+00:00, sha 8f03e6b24353)
- Data as of 2026-08-30T08:39:29.467469+00:00.