Rename scanned documents based on their content (e.g., using OCR): November 16, 2024

Rename Scanned Documents Based on Their Content (e.g., Using OCR)

📁 Did you know that you can rename scanned documents based on their content without having to manually read each file? 🤯 This process is made possible by Optical Character Recognition (OCR) technology, which extracts text from images and allows us to manipulate it. In this blog post, we’ll use Python to rename scanned documents based on their content using OCR. Let’s get started! 💻

Prerequisites

🔧 Before we dive into the code, make sure you have the following installed:

* Python 3.x (we’ll be using Python 3.8 in this example)
* `pytesseract` library (a Python wrapper for Google’s Tesseract OCR engine)
* `pillow` library (for image processing)

If you don’t have these installed, you can easily install them using pip:
“`

pip install pytesseract pillow

“`

Step 1: Set Up Tesseract OCR

🔍 Before we can use OCR, we need to set up Tesseract OCR. If you’re on Windows, Mac, or Linux, you can download the executable from [here](https://github.com/tesseract-ocr/tesseract/blob/master/ FAQ.md#installation). Make sure to place the executable in a directory that’s accessible from your Python script.

Step 2: Process the Scanned Document

📝 Now, we’ll write a Python script to process the scanned document. We’ll use `pillow` to open the image, `pytesseract` to extract the text, and then use the extracted text to rename the file.
“`


import os
import pillow
from pytesseract import image_to_string

# Set the path to the scanned document
document_path = 'path/to/scanned_document.jpg'

# Open the image using Pillow
image = pillow.open(document_path)

# Extract the text using OCR
text = image_to_string(image)

# Rename the file based on the extracted text
new_filename = f'{os.path.splitext(os.path.basename(document_path))[0]}_{text}.jpg'
os.rename(document_path, new_filename)

“`
In this code, we first open the scanned document using `pillow`. Then, we extract the text using OCR with `pytesseract`. The extracted text is stored in the `text` variable. Finally, we use the `os` module to rename the file based on the extracted text.

Step 3: Test the Script

⏰ Now that we have the script written, let’s test it! Run the script and provide the path to the scanned document as an argument. For example:
“`

python renaming_script.py 'path/to/scanned_document.jpg'

“`
After running the script, check the directory where the scanned document is located. You should see that the file has been renamed based on the extracted text!

Conclusion

🎉 With this script, you can automate the process of renaming scanned documents based on their content using OCR. This is incredibly useful for organizing large collections of scanned documents, such as financial records, receipts, or invoices.

Questions to Ponder

🤔 Do you have a use case for renaming scanned documents based on their content? 📝 Have you used OCR technology before? Share your experiences and insights with us!

Tags

* Python
* OCR
* Tesseract OCR
* Pillow
* Automation
* Document Organization
* Scanned Documents

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