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ocr-document-processor

Extract text and structure from scans, images, and scanned PDFs. Use for OCR, searchable PDFs, table extraction, receipt parsing, and business card parsing.

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Updated
7 months ago
In the catalog since
1 Oct 2026
From
dkyazzentwatwa/chatgpt-skills
Office & Documents
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Skill instructions

Rendered from the published SKILL.md, 28 lines.

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.