How to cartoonize an image with Python

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:

Let’s jump to the code.

<span>import</span> <span>numpy</span> <span>as</span> <span>np</span>
<span>import</span> <span>cv2</span>
<span>import</span> <span>numpy</span> <span>as</span> <span>np</span>
<span>import</span> <span>cv2</span>


import numpy as np
import cv2

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after that we we read our image:

<span>filename</span> <span>=</span> <span>'</span><span>elon.jpeg</span><span>'</span>
<span>filename</span> <span>=</span> <span>'</span><span>elon.jpeg</span><span>'</span>


filename = 'elon.jpeg'

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then we will define our resizeImage :

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

    <span>return</span> <span>resized</span>


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:

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

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

    <span>return</span> <span>contoured_image</span>


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:

<span>def</span> <span>ColorQuantization</span><span>(</span><span>image</span><span>,</span> <span>K</span><span>=</span><span>4</span><span>):</span>
    <span>Z</span> <span>=</span> <span>image</span><span>.</span><span>reshape</span><span>((</span><span>-</span><span>1</span><span>,</span> <span>3</span><span>))</span> 
<span>def</span> <span>ColorQuantization</span><span>(</span><span>image</span><span>,</span> <span>K</span><span>=</span><span>4</span><span>):</span>
    <span>Z</span> <span>=</span> <span>image</span><span>.</span><span>reshape</span><span>((</span><span>-</span><span>1</span><span>,</span> <span>3</span><span>))</span> 


def ColorQuantization(image, K=4):
    Z = image.reshape((-1, 3)) 

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then we convert image to numpy float32:

    <span>Z</span> <span>=</span> <span>np</span><span>.</span><span>float32</span><span>(</span><span>Z</span><span>)</span> 
    <span>Z</span> <span>=</span> <span>np</span><span>.</span><span>float32</span><span>(</span><span>Z</span><span>)</span> 


    Z = np.float32(Z) 

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also we need to define critera and apply kmeans:

    <span>criteria</span> <span>=</span> <span>(</span><span>cv2</span><span>.</span><span>TERM_CRITERIA_EPS</span> <span>+</span> <span>cv2</span><span>.</span><span>TERM_CRITERIA_MAX_ITER</span><span>,</span> <span>10000</span><span>,</span> <span>0.0001</span><span>)</span>
    <span>compactness</span><span>,</span> <span>label</span><span>,</span> <span>center</span> <span>=</span> <span>cv2</span><span>.</span><span>kmeans</span><span>(</span><span>Z</span><span>,</span> <span>K</span><span>,</span> <span>None</span><span>,</span> <span>criteria</span><span>,</span> <span>1</span><span>,</span> <span>cv2</span><span>.</span><span>KMEANS_RANDOM_CENTERS</span><span>)</span>
    <span>criteria</span> <span>=</span> <span>(</span><span>cv2</span><span>.</span><span>TERM_CRITERIA_EPS</span> <span>+</span> <span>cv2</span><span>.</span><span>TERM_CRITERIA_MAX_ITER</span><span>,</span> <span>10000</span><span>,</span> <span>0.0001</span><span>)</span>
    <span>compactness</span><span>,</span> <span>label</span><span>,</span> <span>center</span> <span>=</span> <span>cv2</span><span>.</span><span>kmeans</span><span>(</span><span>Z</span><span>,</span> <span>K</span><span>,</span> <span>None</span><span>,</span> <span>criteria</span><span>,</span> <span>1</span><span>,</span> <span>cv2</span><span>.</span><span>KMEANS_RANDOM_CENTERS</span><span>)</span>


    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:

   <span>center</span> <span>=</span> <span>np</span><span>.</span><span>uint8</span><span>(</span><span>center</span><span>)</span>
   <span>res</span> <span>=</span> <span>center</span><span>[</span><span>label</span><span>.</span><span>flatten</span><span>()]</span>
   <span>res2</span> <span>=</span> <span>res</span><span>.</span><span>reshape</span><span>((</span><span>image</span><span>.</span><span>shape</span><span>))</span>
   <span>return</span> <span>res2</span>
   <span>center</span> <span>=</span> <span>np</span><span>.</span><span>uint8</span><span>(</span><span>center</span><span>)</span>
   <span>res</span> <span>=</span> <span>center</span><span>[</span><span>label</span><span>.</span><span>flatten</span><span>()]</span>
   <span>res2</span> <span>=</span> <span>res</span><span>.</span><span>reshape</span><span>((</span><span>image</span><span>.</span><span>shape</span><span>))</span>

   <span>return</span> <span>res2</span>


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

   return res2

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<span>if</span> <span>__name__</span> <span>==</span> <span>"</span><span>__main__</span><span>"</span><span>:</span>
    <span>image</span> <span>=</span> <span>cv2</span><span>.</span><span>imread</span><span>(</span><span>filename</span><span>)</span>
    <span>resized_image</span> <span>=</span> <span>resizeImage</span><span>(</span><span>image</span><span>)</span>
    <span>coloured</span> <span>=</span> <span>ColorQuantization</span><span>(</span><span>resized_image</span><span>)</span>
    <span>contoured</span> <span>=</span> <span>findCountours</span><span>(</span><span>coloured</span><span>)</span>
    <span>final_image</span> <span>=</span> <span>contoured</span>
    <span>save_q</span> <span>=</span> <span>input</span><span>(</span><span>"</span><span>Save the image? [y]/[n] </span><span>"</span><span>)</span>
    <span>if</span> <span>save_q</span> <span>==</span> <span>"</span><span>y</span><span>"</span><span>:</span>
        <span>cv2</span><span>.</span><span>imwrite</span><span>(</span><span>"</span><span>cartoonized_</span><span>"</span><span>+</span> <span>filename</span><span>,</span> <span>final_image</span><span>)</span>
        <span>print</span><span>(</span><span>"</span><span>Image saved!</span><span>"</span><span>)</span>
<span>if</span> <span>__name__</span> <span>==</span> <span>"</span><span>__main__</span><span>"</span><span>:</span>

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

    <span>if</span> <span>save_q</span> <span>==</span> <span>"</span><span>y</span><span>"</span><span>:</span>

        <span>cv2</span><span>.</span><span>imwrite</span><span>(</span><span>"</span><span>cartoonized_</span><span>"</span><span>+</span> <span>filename</span><span>,</span> <span>final_image</span><span>)</span>
        <span>print</span><span>(</span><span>"</span><span>Image saved!</span><span>"</span><span>)</span>


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:

Thank you all.

原文链接：How to cartoonize an image with Python