OCR and Document Text Extraction

Extract readable text from PDFs, scanned images, and Word documents using Python libraries available in most environments. No cloud API required.

When to Use

• User wants to read text from a PDF file
• User wants to extract text from a scanned image or photo of a document
• User wants to read a .docx Word document programmatically
• User wants to convert a multi-page document to plain text for analysis
• User wants to extract specific pages or sections from a PDF

How to Use

1. Extract text from a PDF (pymupdf, fastest)

import fitz  # pip install pymupdf

doc  = fitz.open("document.pdf")
text = "\n\n".join(page.get_text() for page in doc)
print(text[:2000])  # preview first 2000 chars
doc.close()

2. Extract text from a PDF (pdf-parse via Node.js)

// requires: npm install pdf-parse (already in DevOS dependencies)
const pdfParse = require('pdf-parse')
const fs       = require('fs')
const data     = await pdfParse(fs.readFileSync('document.pdf'))
console.log(data.text.slice(0, 2000))
console.log(`Pages: ${data.numpages}`)

3. OCR a scanned image (Tesseract)

Requires Tesseract installed: winget install UB-Mannheim.TesseractOCR

import pytesseract          # pip install pytesseract
from PIL import Image       # pip install Pillow

img  = Image.open("scan.png")
text = pytesseract.image_to_string(img, lang="eng")
print(text)

4. OCR with preprocessing for better accuracy

import pytesseract
from PIL import Image, ImageFilter, ImageOps

img = Image.open("scan.jpg")
img = ImageOps.grayscale(img)
img = img.filter(ImageFilter.SHARPEN)
img = img.point(lambda p: 255 if p > 128 else 0)  # binarize
text = pytesseract.image_to_string(img, config="--psm 6")
print(text)

5. Extract text from a Word .docx file

from docx import Document   # pip install python-docx