pro-ledin-ocr 0.3.0

Layered OCR workhorse: extract text from scanned PDFs and images (tesseract, PyMuPDF, easyocr, paddleocr, vision-api).

pro-ledin-ocr

Layered OCR workhorse: extract text from scanned PDFs and images (PNG/JPG/TIFF/ HEIC/WEBP) using a tiered engine stack. The baseline path (poppler + tesseract) needs zero extra Python installs; heavier engines are opt-in extras.

• Import name: pro.ledin.ocr
• Console scripts: ocr, ocr-probe, peepshow-sink-ocr
• PyPI: pro-ledin-ocr

Install

pip install pro-ledin-ocr            # baseline
pip install "pro-ledin-ocr[vision]"  # + OpenAI-compatible vision-api engine
pip install "pro-ledin-ocr[all]"     # + pymupdf, opencv, easyocr, paddleocr

System binaries required for the local path: poppler (pdftoppm, pdftotext, pdfinfo) and tesseract (with language packs).

brew install poppler tesseract tesseract-lang      # macOS
sudo apt install poppler-utils tesseract-ocr-all   # Debian/Ubuntu

CLI

ocr-probe myfile.pdf                          # triage: does it need OCR?
ocr myfile.pdf --format all                   # md + txt + json
ocr scan.png --format md
ocr russian_doc.pdf --lang rus+eng --format md
ocr scan.pdf --preprocess full                # deskew + denoise
ocr slides.pdf --engine vision --pages 9,12   # hand pages to a multimodal agent
ocr table.png --engine vision \
  --vision-prompt "Extract only table rows and preserve empty cells"
ocr slides.pdf --engine vision-api \
  --vision-api-url https://api.example.com/v1 \
  --vision-api-key "$KEY" --vision-model my-vision-model \
  --vision-prompt-file prompts/faithful-ocr.txt

See ocr --help for the full flag reference.

Peepshow sink

peepshow-sink-ocr reads peepshow's JSON payload from stdin, recognizes each primary frame, and atomically writes <outputDir>/ocr.json:

peepshow video.mp4 --sink ocr
peepshow video.mp4 \
  --sink-cmd 'peepshow-sink-ocr --engine tesseract --lang rus+eng'

No extra Python dependency is required for the sink interface. Peepshow only needs the installed peepshow-sink-ocr executable on PATH. The default local engine still requires Tesseract; vision-api requires pip install "pro-ledin-ocr[vision]".

Configure named sink runs through PEEPSHOW_SINK_OCR_* variables:

export PEEPSHOW_SINK_OCR_ENGINE=vision-api
export PEEPSHOW_SINK_OCR_VISION_API_URL=https://api.example.com/v1
export PEEPSHOW_SINK_OCR_VISION_API_KEY="$KEY"
export PEEPSHOW_SINK_OCR_VISION_MODEL=my-vision-model
export PEEPSHOW_SINK_OCR_TIMEOUT=120
peepshow video.mp4 --sink ocr

The sink never changes peepshow's manifest or frames and prints no OCR content to stdout. vision-api sends frame images to the configured external endpoint. Protect both API credentials and output directories containing recognized text.

Library

from pro.ledin import ocr

pages = ocr.recognize(
    "scan.pdf",
    ocr.RecognizeOptions(
        engine="vision-api",
        vision_api_key="key",
        vision_model="model",
        vision_prompt="Preserve checkbox states and labels.",
    ),
)
markdown = ocr.to_markdown(pages, "scan.pdf")

recognize() never calls sys.exit(); catch ocr.OcrError for recoverable failures (unsupported input, missing binaries/packages, vision-api config).

Engine tiers

Tier	Engine	Best for	Cost
0	pdftotext / PyMuPDF	Real text layers	Free, instant
1	tesseract (default)	Clean scans, typed text, 160+ languages	Free
2	easyocr	Handwriting, degraded scans	Free, heavy
2.5	paddleocr	CJK, multilingual, angled text	Free
3	vision (agent reads PNGs)	Tables, charts, complex layouts	Agent tokens
3.5	vision-api (OpenAI-compatible)	Headless batch, complex layouts	API cost

Full docs: skills/ocr/SKILL.md, skills/ocr/references/engines.md, skills/ocr/references/peepshow-sinks.md, and skills/ocr/references/troubleshooting.md.

Development

uv sync --extra dev
uv run --extra dev pytest
uv build

License

MIT