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pdf_ocr_artifact_cleaner

Remove OCR artifacts like dehyphenation and page numbers from PDFs.

541|171|Updated May 3, 2018
Search Tags:#ocr#document processing#pdf#artifact removal#text cleaning
One-click install
npx skills add https://github.com/cas-bigdatalab/piflow --skill pdf-ocr-artifact-cleaner
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: pdf_ocr_artifact_cleaner
Source: https://github.com/cas-bigdatalab/piflow/tree/main/workspace/skills/pdf_ocr_artifact_cleaner
Command: npx skills add https://github.com/cas-bigdatalab/piflow --skill pdf-ocr-artifact-cleaner

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill addresses common issues in OCR extraction from PDFs, such as dehyphenation, page number removal, and ligature normalization, improving the accuracy of extracted text.

Core Features & Use Cases

  • Artifact Removal: Corrects common OCR errors like dehyphenation, page number removal, and ligature normalization.
  • Text Cleaning: Enhances the accuracy of extracted text for better data processing.
  • Use Case: When dealing with OCR-generated text from PDFs, this Skill can be used to ensure the text is free from common OCR artifacts, making it more reliable for further processing.

Quick Start

Clean OCR artifacts from your PDF using the pdf_ocr_artifact_cleaner skill. Run the following command: pdf_ocr_artifact_cleaner --input_path path/to/input.pdf --output_path path/to/output.csv

Frequently Asked Questions about pdf_ocr_artifact_cleaner

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I clean OCR artifacts from PDF text extraction?▼

To clean OCR artifacts from PDF text extraction, use a Python-based text manipulation tool that applies pattern matching to correct errors like dehyphenation, page number removal, and ligature normalization, improving extracted text accuracy.

What are common OCR artifacts that need removal from PDF documents?▼

Common OCR artifacts requiring removal from PDF documents include broken hyphens, embedded page numbers, and improperly converted ligatures, which this text cleaning process corrects through Python pattern matching and text manipulation.

How do I remove page numbers and fix hyphenation in OCR PDF output?▼

You can remove page numbers and fix hyphenation in OCR PDF output by running a Python script that performs pattern matching and text manipulation to normalize ligatures and correct dehyphenation artifacts.

Can I use Python to normalize ligatures and clean OCR text for data processing?▼

Yes, you can use Python libraries for file handling and text processing to normalize ligatures and clean OCR text, ensuring the extracted PDF output is reliable for downstream data processing and analysis workflows.

Does this OCR text cleaning approach require any external dependencies?▼

This OCR text cleaning approach relies solely on Python libraries for file handling and text processing, requiring no external dependencies to execute the pattern matching and artifact removal scripts.

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