Sketchify 🎨

An image-to-pencil-sketch converter using computer vision techniques. Transforms any image into a realistic pencil sketch through grayscale conversion, inversion, Gaussian blur, and division blending.

Project Statistics 📊

• 4 processing steps (Grayscale → Inversion → Blur → Division Blending)
• 3 intermediate visualizations (Grayscale, Inverted, Final Sketch)
• Adjustable sketch intensity (default: 220.0)
• Automatic aspect ratio preservation (max 800x600)
• 21x21 Gaussian kernel for smooth blur effect
• Real-time processing (near-instant for standard images)

Project Overview 🎯

Sketchify is a learning project built while exploring computer vision, image processing, and OpenCV. It demonstrates fundamental image processing techniques to create artistic pencil sketch effects from photographs.

Development Context

• Built as a hands-on learning project for computer vision and image processing
• Explores OpenCV's image manipulation capabilities
• Demonstrates practical application of grayscale conversion, inversion, and blending techniques
• Foundation for understanding digital image processing algorithms

What I Learned

• Grayscale conversion and color space manipulation
• Image inversion techniques
• Gaussian blur for noise reduction
• Division blending for sketch effects
• Aspect ratio preservation during resizing
• OpenCV window management and display

How It Works 🔧

The sketch conversion process involves 4 key steps:

1. Grayscale Conversion

   • Converts RGB image to grayscale
   • Reduces color information to intensity values

2. Image Inversion

   • Inverts pixel values (255 - pixel_value)
   • Creates negative effect

3. Gaussian Blur

   • Applies 21x21 Gaussian kernel
   • Smooths inverted image
   • Reduces noise and creates soft edges

4. Division Blending

   • Divides grayscale by inverted blur
   • Scale factor: 220.0 (adjustable)
   • Produces pencil sketch effect

Real-World Applications 🚀

• Artists: Reference sketches for drawing practice
• Social Media: Artistic filters for photos
• Education: Learning tool for image processing concepts
• Fun Projects: Creative photo transformations for kids and hobbyists

Installation & Setup 🛠️

Prerequisites

• Python 3.8 or higher
• OpenCV library

Installation

1. Clone the repository:

   git clone https://github.com/patelritiq/Sketchify.git
   cd Sketchify

2. Install OpenCV:

   pip install opencv-python

Usage 📖

1. Place your image in the project folder

2. Update the image path in sketch.py:

   image_path = "your_image.jpg"

3. Run the script:

   python sketch.py

4. View the results:

   • Original image
   • Grayscale version
   • Inverted version
   • Final pencil sketch

5. Press any key to advance through each stage

Configuration ⚙️

You can adjust the sketch intensity by modifying the sketch_intensity variable:

sketch_intensity = 220.0  # Higher = darker sketch, Lower = lighter sketch

Recommended values:

• Light sketch: 180-200
• Normal sketch: 220 (default)
• Dark sketch: 240-260

Technical Details 🔬

Image Processing Pipeline

• Input: RGB image (any size)
• Resize: Max 800x600 (maintains aspect ratio)
• Grayscale: BGR to GRAY conversion
• Inversion: 255 - pixel_value
• Blur: Gaussian kernel (21x21, sigma=0)
• Blending: Division with scale factor
• Output: Grayscale pencil sketch

Performance

• Processing Time: Near-instant (<1 second for standard images)
• Memory Usage: Minimal (depends on image size)
• Supported Formats: JPG, PNG, BMP, TIFF (all OpenCV-supported formats)

Limitations ⚠️

• Requires manual image path configuration
• Processes one image at a time
• No automatic saving (displays only)
• Fixed Gaussian kernel size
• Limited to grayscale output

Future Enhancements 🔮

• GUI for user-friendly controls
• Batch processing for multiple images
• Automatic output saving
• Adjustable blur kernel size
• Color sketch options
• Real-time webcam sketching
• Command-line arguments
• Different sketch styles (charcoal, ink, etc.)

Troubleshooting 🔧

Issue: "Error: Unable to load image"

Solution:

• Ensure image file exists in the project directory
• Check image filename and extension
• Verify image format is supported by OpenCV

Issue: Sketch too light/dark

Solution:

• Adjust sketch_intensity variable
• Higher values = darker sketch
• Lower values = lighter sketch

Issue: Image too large/small

Solution:

• Modify max_width and max_height variables
• Default: 800x600 pixels

License 📄

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

Author 👨‍💻

Ritik Pratap Singh Patel

• Computer vision and image processing enthusiast
• OpenCV learner

Acknowledgments 🙏

This project was developed as a learning exercise in computer vision and image processing using OpenCV. It demonstrates fundamental techniques for artistic image transformation.

Quick Start 🚀

# Clone repository
git clone https://github.com/patelritiq/Sketchify.git
cd Sketchify

# Install OpenCV
pip install opencv-python

# Run the program
python sketch.py

Transform your photos into artistic pencil sketches! 🎨✨