How to Use OCR to Extract Text from Images Using Termux

Sometimes you have important information in an image—like a receipt, screenshot, or document—and typing it manually is tedious. That’s where OCR (Optical Character Recognition) comes in. With Termux, you can extract text from images directly on your Android device without relying on cloud services. This is fast, private, and perfect for anyone who wants to stay productive on the go.

Why Use OCR on Android with Termux?

There are plenty of apps for OCR, but they often require internet access or send your data to third-party servers. Using Termux keeps everything local, which means your sensitive data stays private. Plus, you can integrate OCR into automated workflows, syncing extracted text to your PC or storing it in structured formats.

If you’re looking to expand your Termux automation skills, check out my guide on quick Termux projects for ideas you can combine with OCR extraction.

Requirements

• Termux installed on your Android device (installation guide)
• Python 3 installed in Termux
• tesseract-ocr package for OCR
• Pillow library for handling images in Python
• Basic familiarity with Termux commands

Step 1: Install Required Packages

Open Termux and update your packages first:

pkg update && pkg upgrade -y
pkg install python git tesseract -y
pip install pytesseract pillow

This installs Python, Tesseract OCR engine, and the Pillow library for image processing. Pytesseract acts as a bridge between Python and Tesseract, making it easy to extract text programmatically.

Step 2: Prepare Your Image

For best results, your image should be clear and high-contrast. Place it in a directory you can easily access in Termux, for example, . To access storage, make sure you’ve granted Termux storage permissions:

termux-setup-storage

This allows Termux to read and write files in your shared storage.

Step 3: Write a Python OCR Script

Create a simple Python script to extract text from an image. For example:

import pytesseract
from PIL import Image

# Load your image
image = Image.open("/sdcard/Download/sample-image.png")

# Extract text
text = pytesseract.image_to_string(image)

# Print result
print("Extracted Text:")
print(text)

Save this script as ocr_extract.py and run it in Termux using:

python ocr_extract.py

You’ll see the extracted text printed in the terminal. From here, you can save it to a file, send it via email, or even sync it to your PC using wireless file syncing in Termux.

Step 4: Automate OCR Tasks

One of the most powerful things about using Termux for OCR is automation. You can create scripts that process all images in a folder, extract text, and store it in organized files. For example:

import os
import pytesseract
from PIL import Image

folder_path = "/sdcard/Download/ocr_images/"
output_file = "/sdcard/Download/ocr_results.txt"

with open(output_file, "w") as f:
    for file in os.listdir(folder_path):
        if file.endswith(".png") or file.endswith(".jpg"):
            img_path = os.path.join(folder_path, file)
            text = pytesseract.image_to_string(Image.open(img_path))
            f.write(f"--- {file} ---\n{text}\n\n")

print("OCR extraction completed. Results saved to ocr_results.txt")

This script loops through all images in the folder and saves the extracted text in one file. Perfect for batch processing receipts, screenshots, or reports.

Step 5: Enhance Accuracy

OCR accuracy depends on image quality. You can improve results by:

• Converting images to grayscale
• Increasing contrast using Pillow
• Ensuring text is horizontal and not skewed

For example, adding preprocessing in your Python script:

gray_image = image.convert('L') # Convert to grayscale
text = pytesseract.image_to_string(gray_image)

Small tweaks like this can dramatically improve text extraction, especially for scanned documents or low-quality images.

Step 6: Keep Your Workflow Secure

Even though OCR happens locally, it’s still important to follow cybersecurity best practices. Always store sensitive data securely and avoid sharing unencrypted files over public networks. For guidance on securing your mobile and desktop environment, see my posts on IT security and cybersecurity for small companies.

Wrapping Up

Using OCR in Termux is a powerful way to extract text from images without relying on cloud services. Once you’ve set up the workflow, you can automate tasks, improve accuracy with preprocessing, and even integrate extracted text into other Termux projects, like file syncing or report generation. This approach is private, efficient, and perfect for anyone who works with documents and screenshots regularly.

Want to take your Termux skills even further? Check out my guide on mastering information gathering and see how OCR can fit into broader automation and data collection workflows.