Cartoon Filter Application

An advanced image processing application that transforms regular photographs into cartoon-style images using computer vision techniques.

Features

• Multiple Edge Detection Methods: Choose between Canny, Sobel, or Laplacian algorithms
• Bilateral Filtering: Preserve edges while smoothing textures
• Intelligent Color Quantization: K-means or uniform color reduction
• Real-time Parameter Adjustments: See changes as you make them
• Style Presets: Pre-configured settings for different cartoon styles
• Comparison Views: Side-by-side and process step visualization
• Batch Processing: Process multiple images with the same settings

Demo

Installation

1. Clone this repository:

git clone https://github.com/taimoorkhan10/CartoonFilter.git
cd CartoonFilter

2. Install required packages:

pip install -r requirements.txt

Usage

GUI Application

To start the main application with full features:

python main.py

Command Line Interface

For batch processing or automation:

python cli.py -i input_image.jpg -o output_image.png

Use python cli.py --help for more options and parameters.

How It Works

The cartoon effect is created through several image processing steps:

1. Edge Detection: Identifies boundaries in the image using advanced algorithms
2. Bilateral Filtering: Smooths the image while preserving important edges
3. Color Quantization: Reduces the number of colors to create flat regions
4. Color Enhancement: Adjusts saturation to create vibrant cartoon-like colors

The combination of these techniques creates a customizable cartoon effect.

Project Structure

• app.py - Main GUI application
• cartoon_filter.py - Core image processing functionality
• preset_loader.py - Handles saving and loading style presets
• main.py - Application entry point
• cli.py - Command-line interface
• utils.py - Helper functions and utilities
• presets.json - Pre-defined style configurations

Available Presets

• Default: Balanced cartoon effect
• Bold Lines: Stronger outlines
• Sketch: Black and white drawing style
• Minimal: Simple style with fewer details
• Vibrant: Bright colors with medium lines
• Comic: Bold comic book style
• Detailed: More details and fine lines
• Smooth: Soft edges with simplified colors

Contributing

Contributions are welcome! Please feel free to submit a pull request.

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

License

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

Acknowledgments

• OpenCV for providing powerful image processing capabilities
• The Python community for excellent documentation and support
• Digital Image Processing researchers for the algorithms that make this possible

Author

Taimoor Khan - GitHub Profile

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Made with ❤️ for Digital Image Lab