PDF OCR Extractor

Use this skill to extract text from scanned PDFs or image-based PDFs that lack a native text layer. It's completely free, doesn't utilize third-party APIs, and offers unlimited usage. It renders PDF pages to images and runs optical character recognition (OCR).

Dependencies

This skill requires:

1. System Binary:

   tesseract

   (along with required language data packs like

   chi_sim

   or

   eng

   ).
2. Python Packages:

   pypdfium2

   ,

   pytesseract

   , and

   Pillow

   .

Note: Do not run automated

pip install

commands at runtime. Rely on the user or the environment to pre-install the dependencies defined in the metadata block.

Quick Start

Create a Python script (e.g.,

extract.py

) in a temporary directory to handle the extraction safely:

import pypdfium2 as pdfium
import pytesseract
from PIL import Image
import sys
import os

def extract(pdf_path):
    doc = pdfium.PdfDocument(pdf_path)
    full_text = []
    for i, page in enumerate(doc):
        # Render page to a high-resolution image
        bitmap = page.render(scale=2)
        tmp_img = f"/tmp/page_{i}.png"
        bitmap.to_pil().save(tmp_img)
        
        # Run OCR (assuming English and Simplified Chinese packs are installed)
        text = pytesseract.image_to_string(Image.open(tmp_img), lang='chi_sim+eng')
        full_text.append(text)
        
        # Cleanup temporary file
        os.remove(tmp_img)
        
    return "\n".join(full_text)

if __name__ == "__main__":
    if len(sys.argv) > 1:
        print(extract(sys.argv[1]))

Then execute the script:

python3 extract.py /path/to/document.pdf

Security & Sandbox Constraints

• Write temporary images only to

  /tmp/

  and clean them up immediately after extraction.
• Do not attempt to dynamically download or install language packs via shell commands; notify the user if a specific language is missing.