Extract the text From image to pdf and word file Using Python Tkinter

Discover how to easily Extract the text From image using python to pdf and word file. This guide shows you how to build a Python Tkinter application that extracts text from images and saves it into Word or PDF files effortlessly.

Introduction

Manually extracting text from images can be a tedious task. Thankfully, Python offers powerful libraries like pytesseract and Tkinter to automate this process. In this tutorial, you’ll learn how to Extract the text From an image to pdf and word file by creating an easy-to-use desktop application. This project is perfect for beginners exploring GUI development and OCR (Optical Character Recognition).

 

Technologies Used

  • Python – Programming language
  • Tkinter – GUI toolkit for Python
  • pytesseract – Optical Character Recognition (OCR) tool
  • Pillow – Image processing library
  • fpdf – PDF creation library
  • python-docx – Word document generation library

 

Installation Guide for Technologies Used

Before building the project to Extract the Text from an Image Using Python, make sure to install the following required libraries and tools.

1. Install Python

Make sure you have Python installed. You can download it from the official site: Download Python.

2. Install Required Python Libraries
# Install tkinter (already included with Python on most systems)
# For Linux, you can install manually:
sudo apt-get install python3-tk

# Install pytesseract
pip install pytesseract

# Install Pillow for image processing
pip install Pillow

# Install fpdf to create PDF files
pip install fpdf

# Install python-docx to create Word documents
pip install python-docx
3. Install Tesseract-OCR Engine

Since pytesseract is only a wrapper, you also need to install the Tesseract-OCR engine:

  • Windows: Download from Tesseract GitHub and install.
  • Linux (Ubuntu/Debian): sudo apt install tesseract-ocr
  • macOS (using Homebrew): brew install tesseract
4. Set Tesseract Path in Python Code
pytesseract.pytesseract.tesseract_cmd = r"C:\Program Files\Tesseract-OCR\tesseract.exe"

Adjust the path if you installed Tesseract in a different location.

5. (Optional) Create a requirements.txt

To install all packages at once, you can create a requirements.txt file with the following content:

pytesseract
Pillow
fpdf
python-docx

Then run:

pip install -r requirements.txt

Now your Python environment is fully ready to build the project and extract text from images easily!

Project Overview: Extract the text From an image to pdf and word file

This simple Python application allows users to:

  1. Select an image (formats: PNG, JPG, BMP, TIFF)
  2. Extract text using OCR
  3. View extracted text in a scrollable text box
  4. Save extracted text as a Word (.docx) file
  5. Save extracted text as a PDF (.pdf) file

How It Works

1. Selecting an Image

Click the “Select Image” button to open a file dialog where you can choose an image file. The application supports PNG, JPG, BMP, and TIFF formats.

2. Extracting Text

After selecting an image, click “Extract Text”. The app uses Tesseract OCR to scan the image and retrieve all readable text, which is displayed inside a scrollable text widget.

3. Saving as Word or PDF

Once the text is extracted, you can choose to save it as a Word document or a PDF file. The application ensures Unicode font support for multi-language text.

Key Code Snippets

Selecting an Image File
filepath = filedialog.askopenfilename(
    filetypes=[("Image Files", "*.png *.jpg *.jpeg *.bmp *.tiff")]
)
Extracting Text Using pytesseract
img = Image.open(image_path)
text = pytesseract.image_to_string(img)
Saving Text as a Word Document
doc = Document()
doc.add_paragraph(text)
doc.save(filepath)
Saving Text as a PDF Document
pdf = FPDF()
pdf.add_page()
pdf.add_font('DejaVu', '', font_path, uni=True)
pdf.set_font('DejaVu', '', 12)
for line in text.split('\n'):
    pdf.multi_cell(0, 10, line)
pdf.output(filepath)
Benefits of Automating Text Extraction
  • Saves time compared to manual typing
  • Improves data entry accuracy
  • Streamlines document management
  • Boosts productivity for businesses and individuals

Complete Code extract-text.py

import tkinter as tk
from tkinter import filedialog, messagebox, ttk
from tkinter.scrolledtext import ScrolledText
from PIL import Image
import pytesseract
from docx import Document
from fpdf import FPDF
import os
import threading

# Set path to tesseract.exe
pytesseract.pytesseract.tesseract_cmd = r"C:\Program Files\Tesseract-OCR\tesseract.exe"  # Adjust if needed

def select_image():
    filepath = filedialog.askopenfilename(
        title="Select an image file",
        filetypes=[("Image Files", "*.png *.jpg *.jpeg *.bmp *.tiff")]
    )
    if filepath:
        entry_file.delete(0, tk.END)
        entry_file.insert(0, filepath)

def extract_text_threaded():
    threading.Thread(target=extract_text).start()

def extract_text():
    image_path = entry_file.get()
    if not os.path.exists(image_path):
        messagebox.showerror("Error", "Image file does not exist!")
        return

    try:
        progress_bar.place(relx=0.5, rely=0.5, anchor="center")  # Centered inside text box
        progress_bar.start()

        img = Image.open(image_path)
        text = pytesseract.image_to_string(img)

        if not text.strip():
            messagebox.showinfo("No Text", "No text detected in the image.")
            return

        text_box.config(state=tk.NORMAL)
        text_box.delete(1.0, tk.END)
        text_box.insert(tk.END, text)
        text_box.config(state=tk.NORMAL)

    except Exception as e:
        messagebox.showerror("Error", str(e))
    finally:
        progress_bar.stop()
        progress_bar.place_forget()  # Hide progress bar

def save_as_word():
    text = text_box.get(1.0, tk.END).strip()
    if not text:
        messagebox.showwarning("Warning", "No text to save!")
        return

    filepath = filedialog.asksaveasfilename(
        defaultextension=".docx",
        filetypes=[("Word Document", "*.docx")]
    )
    if filepath:
        try:
            doc = Document()
            doc.add_paragraph(text)
            doc.save(filepath)
            messagebox.showinfo("Saved", f"Text saved as Word file:\n{filepath}")
        except Exception as e:
            messagebox.showerror("Error", str(e))

def save_as_pdf():
    text = text_box.get(1.0, tk.END).strip()
    if not text:
        messagebox.showwarning("Warning", "No text to save!")
        return

    filepath = filedialog.asksaveasfilename(
        defaultextension=".pdf",
        filetypes=[("PDF file", "*.pdf")]
    )
    if filepath:
        try:
            pdf = FPDF()
            pdf.add_page()
            
            # Add a Unicode font (DejaVuSans.ttf must be in the same folder)
            font_path = os.path.join(os.path.dirname(__file__), r"D:\Python\extract-text\DejavuSans.ttf")
            pdf.add_font('DejaVu', '', font_path, uni=True)
            pdf.set_font('DejaVu', '', 12)
            
            for line in text.split('\n'):
                pdf.multi_cell(0, 10, line)

            pdf.output(filepath)
            messagebox.showinfo("Saved", f"Text saved as PDF file:\n{filepath}")
        except Exception as e:
            messagebox.showerror("Error", str(e))


# Helper function to get correct path for icon
def resource_path(relative_path):
    try:
        # PyInstaller creates a temp folder and stores path in _MEIPASS
        base_path = sys._MEIPASS
    except Exception:
        base_path = os.path.abspath(".")
    return os.path.join(base_path, relative_path)

# --- GUI ---
root = tk.Tk()
root.title("Image to Text Extractor")
root.minsize(400, 600)  # Minimum window size

frame = tk.Frame(root, padx=10, pady=10)
frame.pack(fill=tk.BOTH, expand=True)

# Widgets
btn_select = tk.Button(frame, text="Select Image", command=select_image)
entry_file = tk.Entry(frame, width=50)
btn_extract = tk.Button(frame, text="Extract Text", command=extract_text_threaded)

text_frame = tk.Frame(frame)
text_box = ScrolledText(text_frame, width=80, height=20, wrap=tk.WORD)

progress_bar = ttk.Progressbar(text_frame, orient=tk.HORIZONTAL, mode='indeterminate', length=200)
progress_bar.place_forget()

btn_save_word = tk.Button(frame, text="Save as Word", command=save_as_word)
btn_save_pdf = tk.Button(frame, text="Save as PDF", command=save_as_pdf)

# Layout function (dynamic)
def layout_widgets(event=None):
    width = root.winfo_width()

    # Clear old layout
    for widget in frame.winfo_children():
        widget.grid_forget()
        widget.pack_forget()

    if width < 500:  # Mobile Layout
        btn_select.pack(pady=5, fill=tk.X)
        entry_file.pack(pady=5, fill=tk.X)
        btn_extract.pack(pady=5, fill=tk.X)

        text_frame.pack(pady=10, fill=tk.BOTH, expand=True)
        text_box.pack(fill=tk.BOTH, expand=True)

        btn_save_word.pack(pady=5, fill=tk.X)
        btn_save_pdf.pack(pady=5, fill=tk.X)

    else:  # Desktop Layout
        btn_select.grid(row=0, column=0, padx=5, pady=5)
        entry_file.grid(row=0, column=1, padx=5, pady=5, sticky="ew")
        btn_extract.grid(row=0, column=2, padx=5, pady=5)

        frame.grid_columnconfigure(1, weight=1)

        text_frame.grid(row=1, column=0, columnspan=3, pady=10, sticky="nsew")
        text_box.pack(fill=tk.BOTH, expand=True)

        btn_save_word.grid(row=2, column=0, pady=5)
        btn_save_pdf.grid(row=2, column=2, pady=5)

    # Make sure frame expands correctly
    frame.pack(fill=tk.BOTH, expand=True)

# Bind resize event
root.bind("", layout_widgets)

# Initialize layout
layout_widgets()

root.mainloop()

Output

Conclusion

By completing this project, you now know how to Extract the text From an image to pdf and word file using a Python Tkinter GUI application. This hands-on project introduces you to OCR technology and file conversion, which are valuable skills for automating tasks and improving workflow efficiency. You can extend this app by adding features like multi-image processing or cloud uploads to make it even more powerful!

📥
Click here to Download
 the source code or ask questions in the comments below!

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