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SnapOtter/apps/docs/tools/pdf/ocr-pdf.md
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SnapOtterandGitHub 991c981529 fix: make OCR portable and reliable across AMD64 and ARM64 (#519)
* fix: make OCR portable and reliable

* fix: harden OCR installation portability

* fix: pin OCR partials across downloads

* fix: make OCR execution reliably asynchronous

* fix: harden OCR portability and docs routes

* fix: preserve decoder and docs safeguards
2026-07-15 03:34:24 +08:00

4.0 KiB

description
description
Extract text from scanned PDFs locally with built-in Tesseract or the optional high-accuracy RapidOCR runtime.

PDF OCR

Extract text from scanned PDF documents page by page without sending the PDF to an external service. The built-in fast tier uses Tesseract. The optional balanced and best tiers use RapidOCR with pinned PP-OCR ONNX models.

API Endpoint

POST /api/v1/tools/pdf/ocr-pdf

Accepts multipart form data with a PDF file and an optional JSON settings field.

Parameters

Parameter Type Required Default Description
file file Yes - PDF file (multipart), up to 512 MiB encoded; a lower operator upload limit still applies
quality string No Dynamic OCR quality tier: fast, balanced, or best
language string No "auto" Document language: auto, en, de, fr, es, zh, ja, ko. Fast does not support ko
pages string No "all" Page selection, e.g. "all", "1-3", "1,3,5"
enhance boolean No Tier-dependent Improve local contrast before recognition. Fast applies it directly; Balanced and Best retain the variant only when calibrated scoring improves the result. Defaults to true for best and false for fast/balanced
engine string No - Deprecated compatibility alias. Use quality instead. tesseract maps to fast; the legacy paddleocr value maps to balanced but does not load PaddlePaddle

If quality and the deprecated engine field are both omitted, SnapOtter selects the highest available tier in this order: best, balanced, fast. Korean never selects fast; it uses best, then balanced, or returns the accurate-runtime install or compatibility error.

Example Request

curl -X POST http://localhost:1349/api/v1/tools/pdf/ocr-pdf \
  -H "Authorization: Bearer si_your-api-key" \
  -F "file=@scanned.pdf" \
  -F 'settings={"quality": "best", "language": "en", "pages": "1-5", "enhance": true}'

Example Response

Returns 202 Accepted. Track progress via SSE at /api/v1/jobs/{jobId}/progress.

{
  "jobId": "a1b2c3d4-e5f6-7890-abcd-ef1234567890",
  "async": true
}

Notes

  • Accepted input format: .pdf.
  • fast is built in and adds about 25 MiB to the official image. balanced and best require the optional accurate OCR pack (about 208-234 MiB to download and 409-488 MiB installed, depending on the target).
  • Fast supports auto, en, de, es, fr, zh, and ja, but not Korean (ko). Korean requires the accurate pack and balanced or best.
  • The accurate pack supports official Linux amd64 and arm64 containers and uses ONNX Runtime on CPU, including on NVIDIA hosts. Unsupported hosts receive an explicit incompatibility error for Korean rather than a Fast fallback.
  • An explicitly requested tier is never silently downgraded. If balanced or best is unavailable, the API returns 501 with FEATURE_NOT_INSTALLED or FEATURE_INCOMPATIBLE. Explicit Fast or legacy tesseract with Korean returns FEATURE_INCOMPATIBLE and fast-korean-unsupported before queueing.
  • PDF pages are rasterized at high resolution before OCR. best runs the higher-accuracy medium PP-OCRv6 models and scores orientation and enhancement variants, improving recognition at the cost of speed.
  • The auto language setting enables recognition across the supported script set; an explicit hint can improve results for a known document language.
  • You can target specific pages using ranges ("1-3"), comma-separated lists ("1,3,5"), or "all" for every page.
  • A request can process at most 50 pages. Rasterized scratch data is capped at 512 MiB and the aggregate UTF-8 OCR response is capped at 1,000,000 bytes; over-limit jobs fail rather than returning partial text.
  • For PDFs that already contain selectable text, consider using the faster PDF to Text tool instead.