ocrbridge-ocrmac 2.1.0

ocrmac (Apple Vision) OCR engine for OCR Bridge

OCR Bridge - ocrmac Engine

ocrbridge-ocrmac is an OCR Bridge engine backed by Apple's Vision framework via ocrmac.

Overview

This package plugs into OCR Bridge through Python entry points and provides HOCR output for images and PDFs on macOS.

Entry point registration (from pyproject.toml):

[project.entry-points."ocrbridge.engines"]
ocrmac = "ocrbridge.engines.ocrmac:OcrmacEngine"

Features

• Native Apple OCR via Vision framework
• LiveText mode support on newer macOS versions
• Input formats: JPEG, PNG, TIFF, PDF
• HOCR XML output with bbox and confidence metadata
• Automatic plugin discovery in OCR Bridge

Platform Requirements

• macOS only (runtime enforces Darwin)
• macOS 10.15+ for Vision modes (fast, balanced, accurate)
• macOS 14.0+ for livetext

This package will not run on Linux or Windows.

Installation

pip install ocrbridge-ocrmac

Compatibility quick check:

• Python >=3.10
• macOS >=10.15 (>=14.0 for livetext)
• Key runtime deps: ocrbridge-core>=3.1.0, ocrmac>=0.2.2

Usage

The engine is discovered automatically by OCR Bridge, or you can import and use it directly.

Public API

Stable imports from this package:

• OcrmacEngine
• OcrmacParams
• RecognitionLevel

Parameters

• languages (list[str] | None): IETF BCP 47 codes (for example "en-US", "zh-Hans")
• recognition_level (RecognitionLevel): fast, balanced, accurate, livetext

Defaults:

• languages=None (auto-detect)
• recognition_level=RecognitionLevel.BALANCED

Example

from pathlib import Path

from ocrbridge.engines.ocrmac import OcrmacEngine, OcrmacParams, RecognitionLevel

engine = OcrmacEngine()

# Process with defaults
hocr = engine.process(Path("document.pdf"))

# Process with custom parameters
params = OcrmacParams(
    languages=["en-US", "fr-FR"],
    recognition_level=RecognitionLevel.ACCURATE,
)
hocr = engine.process(Path("document.pdf"), params)

# LiveText (requires macOS 14+)
params_livetext = OcrmacParams(
    languages=["en-US"],
    recognition_level=RecognitionLevel.LIVETEXT,
)
hocr = engine.process(Path("document.pdf"), params_livetext)

Integration (Entry Points)

This package exposes one OCR Bridge engine entry point:

• Group: ocrbridge.engines
• Name: ocrmac
• Target: ocrbridge.engines.ocrmac:OcrmacEngine

Verify discovery in your environment

If the package is installed but not discovered, run:

from importlib.metadata import entry_points

eps = entry_points()
group = "ocrbridge.engines"

if hasattr(eps, "select"):
    engines = eps.select(group=group)
else:
    engines = eps.get(group, [])

for ep in engines:
    print(f"{ep.name} -> {ep.value}")

Supported Input Formats

• .jpg
• .jpeg
• .png
• .pdf
• .tiff
• .tif

Development

This repository uses uv for Python environments/dependencies and mise for task aliases.

Setup

mise run install

Quality and Tests

mise run lint
mise run format
mise run typecheck
mise run test
mise run check
mise run all

Direct equivalents:

uv sync --extra dev
uv run ruff check src tests
uv run ruff format src tests
uv run pyright
uv run pytest

Run a Single Test

Use pytest node IDs:

uv run pytest tests/test_models.py::TestOcrmacParams::test_validate_languages
uv run pytest tests/test_engine_unit.py::TestProcessMethod::test_process_routes_to_pdf_handler

Useful filters:

uv run pytest tests/test_engine_integration.py -m integration
uv run pytest -k livetext

Notes on Output and Processing

• Output is HOCR XML (XHTML doctype + namespace)
• OCR annotations are converted from relative bottom-left coordinates to absolute top-left pixel coordinates
• PDFs are rasterized to page images (300 DPI) and merged back into a multi-page HOCR document

Release and CI

• CI runs on macOS and uses mise tasks for lint/format/typecheck/test
• Releases are automated with python-semantic-release
• Commit messages follow Conventional Commits (validated in CI)

Troubleshooting

• Engine not discovered: confirm you installed in the active environment, then run the discovery snippet above.
• livetext fails: verify macOS major version is 14 or newer.
• Non-macOS runtime: expected failure; this engine intentionally supports macOS only.
• PDF OCR issues: ensure Poppler is available when your workflow depends on PDF rasterization tooling.

Contributing

See CONTRIBUTING.md for contribution workflow and commit message guidance.