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How to cartoonize an image with Python

Stokry
Front_dev | Machine Learning Enthusiast
・2 min read

In this tutorial, I will show you how to give a cartoon-effect to an image in Python with OpenCV.

OpenCV is an open-source python library used for computer vision and machine learning. It is mainly aimed at real-time computer vision and image processing. It is used to perform different operations on images which transform them using different techniques.

Many apps can turn your photos into cartoons, but you can do this on your own with few lines of code Python code.

This is our test image:

enter image description here

Let's jump to the code.

import numpy as np
import cv2
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after that we we read our image:

filename = 'elon.jpeg'
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then we will define our resizeImage :

def resizeImage(image):
    scale_ratio = 0.3
    width = int(image.shape[1] * scale_ratio)
    height = int(image.shape[0] * scale_ratio)
    new_dimensions = (width, height)
    resized = cv2.resize(image, new_dimensions, interpolation = cv2.INTER_AREA)

    return resized
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the we need to find contours:

def findCountours(image):

    contoured_image = image
    gray = cv2.cvtColor(contoured_image, cv2.COLOR_BGR2GRAY) 
    edged = cv2.Canny(gray, 30, 100)
    contours, hierarchy = cv2.findContours(edged, 
    cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
    cv2.drawContours(contoured_image, contours, contourIdx=-1, color=1, thickness=1)
    cv2.imshow('Image after countouring', contoured_image)
    cv2.waitKey(0)
    cv2.destroyAllWindows()

    return contoured_image
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after that, we do a color quantization:

def ColorQuantization(image, K=4):
    Z = image.reshape((-1, 3)) 
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then we convert image to numpy float32:

    Z = np.float32(Z) 
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also we need to define critera and apply kmeans:

    criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 10000, 0.0001)
    compactness, label, center = cv2.kmeans(Z, K, None, criteria, 1, cv2.KMEANS_RANDOM_CENTERS)
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then we convert to uint8 and apply to original image:

   center = np.uint8(center)
   res = center[label.flatten()]
   res2 = res.reshape((image.shape))

   return res2
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if __name__ == "__main__":

    image = cv2.imread(filename)
    resized_image = resizeImage(image)
    coloured = ColorQuantization(resized_image)
    contoured = findCountours(coloured)
    final_image = contoured
    save_q = input("Save the image? [y]/[n] ")

    if save_q == "y":

        cv2.imwrite("cartoonized_"+ filename, final_image)
        print("Image saved!")
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This is our final result:
enter image description here

Thank you all.

Discussion (5)

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wchr profile image
Wachira

What are the minimum laptop or desktop hardware requirements

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stokry profile image
Stokry Author • Edited

Anything that has 8GB of RAM and up

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wchr profile image
Wachira

Thanks, you should put that inside the article, thought some GPU would come in handy but if it's just RAM, that's pretty awesome.

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n00bdevop profile image
Mr. Noob • Edited

can i use my pic stored in my pc and if yes then how ?? please help me please !!!

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qokab profile image
qokab

where does file save?