Tesseract OCR Image Text Extraction

Extract text content from images based on Tesseract.js (the WebAssembly port of the Tesseract OCR engine).

Use Cases

Use when users need "image to text," "OCR recognition," "extract text from images," "screenshot character recognition," "scan to text," or "image text orientation detection."

Core Capabilities

• Recognize text from local images or image URLs
• Support for 100+ languages, with the ability to specify multiple languages simultaneously (e.g., ['eng', 'chi_sim'])
• Support for specifying recognition regions (--rectangle), character whitelists (--whitelist)
• Support for text orientation and script detection (--detect)
• Support for switching page segmentation modes (--psm) and OCR engine modes (--oem)
• Output formats: text (default), hocr, blocks (JSON), tsv

Limitations

• Does not support PDF files
• Does not modify the Tesseract recognition model to improve accuracy
• Requires a Node.js environment (this Skill uses Node.js scripts)

Workflow

1. Confirm Environment

node -v && npm ls tesseract.js 2>/dev/null || echo "tesseract.js not installed"

If not installed:

cd /root/.openclaw/workspace/skills/tesseract-ocr && npm init -y > /dev/null 2>&1 && npm install tesseract.js

2. Execute Recognition

Basic command:

node scripts/ocr.js <image-path-or-url> [--options]

Parameter Descriptions:

Common Examples:

# Basic mixed Chinese-English recognition
node scripts/ocr.js photo.jpg --lang chi_sim+eng

# Recognize digits only (license plates, CAPTCHAs, etc.)
node scripts/ocr.js captcha.png --whitelist 0123456789

# Column-based recognition (suitable for vertical Chinese text)
node scripts/ocr.js scroll.jpg --lang chi_sim --psm 4

# Specify a region for recognition
node scripts/ocr.js receipt.png --rectangle 50,100,400,200

# Detect image text orientation
node scripts/ocr.js rotated.jpg --detect

# Output structured data
node scripts/ocr.js doc.png --output blocks

# Manually specify DPI (avoids "Invalid resolution 0 dpi" warning)
node scripts/ocr.js scan.png --dpi 300

3. Batch Recognition of Multiple Images

To reuse a Worker, the AI should write an inline script:

const { createWorker } = require('tesseract.js');
(async () => {
  const worker = await createWorker('eng');
  for (const img of ['a.png', 'b.png', 'c.png']) {
    const { data: { text } } = await worker.recognize(img);
    console.log(img, '→', text);
  }
  await worker.terminate();
})();

PSM — Page Segmentation Modes

The --psm parameter controls how Tesseract analyzes page layout:

OEM — OCR Engine Modes

Language Code Quick Reference

Full list: tesseract_lang_list.md

Advanced Usage

The following scenarios require the AI to write inline scripts directly rather than using scripts/ocr.js:

• Reusing a Worker after switching languages: Use worker.reinitialize(langs, oem)
• Setting Tesseract parameters: Use worker.setParameters({ tessedit_pageseg_mode: ... })
• Detecting text orientation (requires Legacy engine): Call worker.detect(image) after createWorker('eng', 0, { legacyCore: true, legacyLang: true })
• Processing large numbers of images in parallel: Use createScheduler() + multiple Workers

For complete API reference, see references/api.md.