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// 1. Install dependencies: npm install tesseract.js pdfjs-dist
import { createWorker } from 'tesseract.js';
import fs from 'fs';

async function performOcr(imagePath, langCode = 'eng') {
  // Initialize worker locally
  const worker = await createWorker(langCode);
  
  // Extract optical text layout
  const { data: { text } } = await worker.recognize(imagePath);
  
  await worker.terminate();
  return text;
  }

performOcr('./scanned_sheet.png', 'eng')
  .then(text => {
    console.log('Extracted Text:\n', text);
  })
  .catch(console.error);
            

# 1. Install dependencies: pip install pytesseract pillow pdf2image
import pytesseract
from PIL import Image

def perform_ocr(image_path, lang_code='eng'):
    # Open scanned image canvas
    img = Image.open(image_path)
    
    # Run local OCR model pipeline
    text = pytesseract.image_to_string(img, lang=lang_code)
    return text

try:
    extracted_text = perform_ocr('scanned_sheet.png', 'eng')
    print('Extracted Text:\n', extracted_text)
except Exception as e:
    print('OCR failed:', e)
            

# 1. Install tesseract CLI locally:
# Ubuntu: sudo apt install tesseract-ocr
# macOS: brew install tesseract
# Windows: winget install UB-Mannheim.TesseractOCR

# 2. Extract layout characters from scanned sheet directly into output.txt:
tesseract scanned_sheet.png output -l eng

# 3. Read extracted results:
cat output.txt