OCR Document Processor

Handle OCR-heavy inputs where text must be recovered from images or scanned pages.

Use This For

• OCR on images and scanned PDFs
• Searchable PDF export
• Structured extraction to text, markdown, JSON, or HTML
• Table extraction from scanned material
• Receipt parsing and business card parsing

Workflow

1. Decide whether plain OCR, structured extraction, or document-specific parsing is needed.
2. Preprocess noisy inputs before extraction when skew, blur, or shadows are present.
3. Use scripts/ocr_processor.py for core OCR tasks.
4. Use the focused helpers when the input is specialized:
   • scripts/business_card_scanner.py
   • scripts/receipt_scanner.py
5. Return confidence caveats when the source is low quality, rotated, handwritten, or multilingual.

Guardrails

• Prefer explicit language selection when accuracy matters.
• Do not claim fields are exact when OCR confidence is weak.
• Route non-scanned digital PDFs to document-converter-suite instead of OCR by default.