PDF Word Counter

5 Other Ways to Count Words in PDF Documents

While using an online tool offers unmatched accuracy and convenience, there are situations where you may need to manually count the words in a PDF document. 

If you’re looking for alternative methods due to your document’s format, specific workflow requirements, or advanced processing needs, here are five additional ways to accurately count words in a PDF.

1. Counting Words in a PDF Using Adobe Acrobat

Ensure you have Adobe Acrobat Pro DC installed (the free version, Adobe Acrobat Reader, does not support text extraction).

Since Adobe Acrobat doesn’t have a built-in word counter, you need to convert the PDF into a text-based format for word counting.

Option 1: Save as a TXT File (Best for Plain Text PDFs)

Option 2: Save as a Word Document (Best for PDFs with Formatting)

Once you have converted the PDF to TXT or Word format, open it in a word processor like:

Now that the text is extracted, you can count words using the word count feature in your text editor:

2. Convert a PDF to Word and Use Microsoft Word to Count Words

3. Count Words in a PDF Using Google Docs

4. Count Words in a PDF Using Python

For developers, data analysts, and tech-savvy users, Python provides a powerful and automated way to count words in PDFs, ideal for bulk processing. Using Python libraries like PyPDF2, you can extract text, count words programmatically, and integrate it into automation workflows.

This method is efficient for large datasets, multiple PDFs, or repetitive tasks where manual counting is time-consuming.

To extract text from a PDF, install PyPDF2:

pip install PyPDF2

Use the following script to extract text and count words:

import PyPDF2  

def count_words_in_pdf(pdf_path):  
    with open(pdf_path, 'rb') as pdf_file:  
        pdf_reader = PyPDF2.PdfReader(pdf_file)  
        text = " ".join(page.extract_text() or "" for page in pdf_reader.pages)  
    return len(text.split())  

pdf_path = "example.pdf"  
print("Total Word Count:", count_words_in_pdf(pdf_path))  

Save the script as count_pdf_words.py, navigate to its folder, and run:

python count_pdf_words.py

For improved accuracy, use:

pdfplumber for better text extraction:

pip install pdfplumber

pytesseract + pdf2image for OCR on scanned PDFs:

pip install pytesseract pdf2image

Process multiple PDFs at once by looping through a folder of files.

5. Counting Words in Scanned PDFs Using Optical Character Recognition (OCR)

If your PDF file consists of scanned pages, handwritten notes, or images of text, standard word-counting tools will not work because the text is not selectable.

In such cases, you need Optical Character Recognition (OCR) software to extract text from images and convert it into an editable format like TXT or Word, allowing you to count the words accurately.

This method is essential for digitizing printed documents, converting scanned books into text, and analyzing historical records that exist as image-based PDFs.

To extract text from scanned PDFs, you need an OCR (Optical Character Recognition) tool. Some of the best options include:

OCR Tool	Type	Best For
Adobe Acrobat Pro	Paid	High accuracy, professional use
Tesseract OCR	Free (Open-source)	Developers, automated processing
OnlineOCR.net	Free (Online)	Quick one-time conversions
Microsoft OneNote	Free	Basic OCR for handwritten notes
ABBYY FineReader	Paid	Advanced document recognition

Choose an OCR tool based on your needs, file size, and accuracy requirements.

Once you have chosen your OCR software, follow these steps to extract the text:

Using Adobe Acrobat Pro (Best for Accuracy & Professional Use)

Using Tesseract OCR (Best for Developers & Free Automation)

Install Tesseract OCR by running the following command:

pip install pytesseract pdf2image

Use the following Python script to extract text:

import pytesseract
from pdf2image import convert_from_path  

def extract_text_from_scanned_pdf(pdf_path):
    images = convert_from_path(pdf_path)
    text = ""
    for img in images:
        text += pytesseract.image_to_string(img) + " "
    return text  

pdf_path = "scanned_document.pdf"
extracted_text = extract_text_from_scanned_pdf(pdf_path)
print("Extracted Text:", extracted_text)
print("Word Count:", len(extracted_text.split()))

The script extracts text from scanned images, making it editable and countable.

Using OnlineOCR.net (Best for Quick Online Conversion)

Once the OCR software converts the scanned PDF into editable text, you can count words using: