# tleyden/open-ocr

Run your own OCR-as-a-Service using Tesseract and Docker

Repository: https://github.com/tleyden/open-ocr
Canonical: https://ross.abutalabs.com/products/open-ocr
Language: Go
License: Apache-2.0
License Family: permissive
Last push: 2023-09-15T05:11:05+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 4498, "days_push": 1083, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1373, forks 223 (observed 2026-08-28T04:04:32.903239+00:00)

## What it is
OpenOCR is a self-hosted OCR-as-a-Service REST API built in Go on top of Tesseract, containerized with Docker. It uses RabbitMQ for scalable message passing between HTTP and worker components and supports 31+ languages, PDF input, and image preprocessing chains.

## Use cases
- host my own ocr rest api
- extract text from images with tesseract
- convert scanned pdfs to text via api
- run ocr service on kubernetes
- ocr images in multiple languages
- self-hosted ocr microservice with docker

## When to choose
- you want a self-hosted OCR REST API instead of a paid cloud OCR service
- you need scalable, queue-based OCR processing with Docker or Kubernetes
- you need multilingual OCR or PDF-to-text support

## When to avoid
- you need state-of-the-art OCR accuracy beyond Tesseract's capabilities
- you want a simple library to embed OCR in a single process rather than run a distributed service
- you need actively developed features - the project is in maintenance mode

## Facets
- artifact type: service
- maturity: maintenance
- function: ocr, http-server, message-queue, image-processing, pdf
- domain: computer-vision, self-hosted, apis
- platform: go, self-hosted
- tags: tesseract, ocr-as-a-service, rest-api, rabbitmq, microservices, docker, kubernetes, linux

## Member repositories
- tleyden/open-ocr (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:32.903239+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 2026-08-30T04:40:43.894267+00:00, confidence not recorded.
  - readme: https://github.com/tleyden/open-ocr (fetched 2026-08-28T04:04:32.903239+00:00, sha c2f863ca3f57)
- Data as of 2026-08-30T08:39:29.467469+00:00.