Using Pixel_labels, How To Separate Objects In An Image By Color, Which Will Result In Three Images In Python

I am using Kmeans algorithm for creating clusters in an image but I wanted to display seperate clusters of an image. Example if value of K=3 for an image then I wanted to save each

Solution 1:

Let's start with paddington on the left, and assume you have k-means clustered him down to 3 colours on the right/second image:

Now we find the unique colours, and iterate over them. Inside the loop, we use np.where() to set all pixels of the current colour to white and all others to black:

#!/usr/bin/env python3import cv2
import numpy as np

# Load kmeans output image
im = cv2.imread('kmeans.png')

# Get list of unique colours
uniquecols = np.unique(im.reshape(-1,3), axis=0) 

# Iterate over unique coloursfor i, c inenumerate(uniquecols):
    filename = f"colour-{i}.png"print(f"Processing colour {c} into file {filename}")

    # Make output image white wherever it matches this colour, and black elsewhere
    result = np.where(np.all(im==c,axis=2)[...,None], 255, 0)
    cv2.imwrite(filename, result)

Sample Output

Processing colour [483835] into file colour-0.png
Processing colour [138140152] into file colour-1.png
Processing colour [20815490] into file colour-2.png

And the three images are:

---

Change the np.where() line as follows if you prefer the alternative output:

# Make output image white wherever it doesn't match this colourresult = np.where(np.all(im==c,axis=2)[...,None], c, 255)

Keywords: Image, image processing, k-means clustering, colour reduction, color reduction, Python, OpenCV, color separation, unique colours, unique colors.