Cartoonizing an Image Using Opencv

A Streamlit-based application that allows users to upload an image and apply one of three cartoonization techniques to transform it into a stylized cartoon version.

Table of Contents

• About the Project
  • What Cartoonizer Techniques are Used?
  • How It Works:
• Features
• Getting Started
  • Prerequisites
• Installation
• Running Script
• Expectations When Running This App
• Demo
• Acknowledgments
• License

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About the Project

What Cartoonizer Techniques are Used?

This Cartoonizer App is a simple yet powerful image processing tool that applies different cartoonization techniques to an uploaded image. It uses OpenCV and Streamlit for performance, visualization, and user interaction.

How It Works:

The app applies one of the following techniques to generate a cartoon-style version of the input image:

1. Bilateral Filtering + Edge Detection – Smooths and sharpens edges for a cartoon-like effect.
2. Color Quantization + Edge Enhancement – Reduces colors and sharpens edges for a more stylized look.
3. Laplacian Edge Detection – Uses edge detection to enhance sharpness and detail.

The user can select a technique, upload an image, and view both the original and cartoonized versions on the app.

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Features

• Easy-to-use Streamlit interface.
• Supports common image formats: .jpg, .jpeg, and .png.
• Three different cartoonization techniques:
  • Bilateral Filtering + Edge Detection
  • Color Quantization + Edge Enhancement
  • Laplacian Edge Detection
• Real-time preview of the original and cartoonized image.

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Getting Started

Prerequisites

Before you begin, ensure you have the following installed:

Dependency	Version
Python	3.8+
Streamlit	≥1.20
OpenCV	≥4.5
Pillow	≥9.1

You can install them using pip:

pip install streamlit opencv-python pillow

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Installation

To install and run the app locally:

# Clone this repository (if needed)
git clone https://github.com/YOUR_GITHUB_USERNAME/img-cartoonizer-using-opencv.git
cd img-cartoonizer-using-opencv

# Install dependencies
pip install streamlit opencv-python pillow

# Run the app
streamlit run app.py

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Running Script

Once installed, simply run the following command in your terminal:

streamlit run app.py

This will launch the Streamlit application in your browser, where you can interact with the app.

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Expectations When Running This App

• The user must upload an image in .jpg, .jpeg, or .png format.
• One of the three cartoonization techniques must be selected from the dropdown menu.
• The output will display both the original and cartoonized versions of the image side-by-side.

⚠️ If no file is uploaded or a method is not selected, the app will not show any processed image.

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Demo

Here’s a quick overview of how the app looks in action:

1. Open your browser and go to http://localhost:8501 (or the URL provided by Streamlit).
2. Upload an image.
3. Select a cartoonization method.
4. View the original and processed images on the web app UI.

cartoonizing-image.mp4

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Acknowledgments

• Streamlit – For the easy-to-use UI.
• OpenCV – For powerful image processing capabilities.
• Pillow (PIL) – For handling and displaying images in the app.

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License

This project is licensed under the MIT License — see the LICENSE file for details.

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