Dominant Colors in an image using python opencv and scikit-learn

dominat-colors.py

import cv2
from sklearn.cluster import KMeans

class DominantColors:

    CLUSTERS = None
    IMAGE = None
    COLORS = None
    LABELS = None
    
    def __init__(self, image, clusters=3):
        self.CLUSTERS = clusters
        self.IMAGE = image
        
    def dominantColors(self):
    
        #read image
        img = cv2.imread(self.IMAGE)
        
        #convert to rgb from bgr
        img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
                
        #reshaping to a list of pixels
        img = img.reshape((img.shape[0] * img.shape[1], 3))
        
        #save image after operations
        self.IMAGE = img
        
        #using k-means to cluster pixels
        kmeans = KMeans(n_clusters = self.CLUSTERS)
        kmeans.fit(img)
        
        #the cluster centers are our dominant colors.
        self.COLORS = kmeans.cluster_centers_
        
        #save labels
        self.LABELS = kmeans.labels_
        
        #returning after converting to integer from float
        return self.COLORS.astype(int)

img = 'colors.jpg'
clusters = 5
dc = DominantColors(img, clusters) 
colors = dc.dominantColors()
print(colors)