image-ocr

Extract text from JPG, PNG, and WEBP images via Tesseract OCR.

Updated Jan 15, 2026
One-click install
npx skills add https://github.com/KaiserWhoLearns/skillsbench --skill image-ocr-kaiserwholearns
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: image-ocr
Source: https://github.com/KaiserWhoLearns/skillsbench/tree/main/tasks/jpg-ocr-stat/environment/skills/image-ocr
Command: npx skills add https://github.com/KaiserWhoLearns/skillsbench --skill image-ocr-kaiserwholearns

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

OCR converts images containing text into machine-readable text, saving manual transcription time and enabling searchable archives.

Core Features & Use Cases

  • OCR via Tesseract using Python (pytesseract) on common image formats (JPG, PNG, WEBP).
  • Outputs plain text or structured data with metadata like detected language and region counts.
  • Use Case: Process scanned documents, receipts, and screenshots to extract text for indexing, data entry, and archival.

Quick Start

Provide an image file path and receive the extracted text and metadata.

Frequently Asked Questions about image-ocr

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

FAQPage Schema
How do I extract text from images using Python OCR?

Batch processing for OCR text extraction handles multiple scanned documents or receipts simultaneously using Python workflows, outputting structured JSON results containing detected language, region counts, and confidence metadata for automated data entry.

Can I use Tesseract to extract text from scanned receipts and screenshots?

Pytesseract OCR extraction requires installing the Tesseract engine alongside Python dependencies like Pillow for image preprocessing, yielding structured text outputs with language, region, and confidence metadata for accurate data indexing.

Does Python image OCR output structured data with language and confidence metadata?

Python OCR via pytesseract handles common image formats including JPG, PNG, and WEBP. It applies basic image preprocessing steps to extract readable text, delivering structured JSON results with language, region, and confidence metadata.

Do I need Pillow and pytesseract for image preprocessing and text extraction?

OCR text extraction handles batch processing of multiple images simultaneously using Python-based workflows, converting scanned documents and screenshots into structured JSON results with language, region, and confidence metadata for searchable archives.