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ocr-document

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Extract text from PDFs, images, and scanned documents. Uses pymupdf (local) or optional cloud OCR APIs.

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Source SKILL.md: https://github.com/fuyuxiang/echo-agent/blob/HEAD/skills/productivity/ocr-document/SKILL.md

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OCR & Document Processing

Extract text from PDFs, scanned images, and documents.

PDF Text Extraction (PyMuPDF)

Best choice for text-based PDFs:

pip install pymupdf

import pymupdf

doc = pymupdf.open("file.pdf")
for page in doc:
    text = page.get_text()
    print(text)

# All pages at once
full_text = "\n".join(page.get_text() for page in doc)

PDF → Markdown (marker-pdf)

High-quality conversion preserving structure:

pip install marker-pdf
marker_single file.pdf output_dir/ --output_format markdown

Image OCR

Surya OCR (Modern ML-based, best for Chinese)

pip install surya-ocr
surya_ocr image.png --langs zh,en

Pytesseract (Traditional, widely available)

# Install Tesseract engine first
brew install tesseract tesseract-lang  # macOS
apt install tesseract-ocr tesseract-ocr-chi-sim  # Linux
pip install pytesseract Pillow

import pytesseract
from PIL import Image

text = pytesseract.image_to_string(
    Image.open("scan.png"),
    lang="chi_sim+eng"
)

Script

python3 scripts/extract_document.py document.pdf
python3 scripts/extract_document.py scan.png
python3 scripts/extract_document.py report.pdf --output extracted.txt

Auto-detects format by extension: PDF → pymupdf, DOCX → python-docx, Image → pytesseract. OCR language is controlled by system Tesseract config (e.g., chi_sim+eng default).

Tips

  • For scanned PDFs, extract images first then OCR each page
  • Preprocessing (deskew, contrast) improves OCR accuracy
  • Chinese OCR: surya-ocr > pytesseract for accuracy