Created DominantColors class

+import cv2
+import numpy as np
+from sklearn.cluster import KMeans
+import matplotlib.pyplot as plt
+from mpl_toolkits.mplot3d import Axes3D
+
+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)
+        img = 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)
+
+
+    def rgb_to_hex(self, rgb):
+        return '#%02x%02x%02x' % (int(rgb[0]), int(rgb[1]), int(rgb[2]))
+
+
+    def plotClusters(self):
+        #plotting
+        fig = plt.figure()
+        ax = Axes3D(fig)
+        for label, pix in zip(self.LABELS, self.IMAGE):
+            ax.scatter(pix[0], pix[1], pix[2], color = self.rgb_to_hex(self.COLORS[label]))
+        plt.show()
+
+
+    def plotHistogram(self):
+
+        #labels form 0 to no. of clusters
+        numLabels = np.arange(0, self.CLUSTERS+1)
+
+        #create frequency count tables
+        (hist, _) = np.histogram(self.LABELS, bins = numLabels)
+        hist = hist.astype("float")
+        hist /= hist.sum()
+
+        #appending frequencies to cluster centers
+        colors = self.COLORS
+
+        #descending order sorting as per frequency count
+        colors = colors[(-hist).argsort()]
+        hist = hist[(-hist).argsort()]
+
+        #creating empty chart
+        chart = np.zeros((50, 500, 3), np.uint8)
+        start = 0
+
+        #creating color rectangles
+        for i in range(self.CLUSTERS):
+            end = start + hist[i] * 500
+
+            #getting rgb values
+            r = colors[i][0]
+            g = colors[i][1]
+            b = colors[i][2]
+
+            #using cv2.rectangle to plot colors
+            cv2.rectangle(chart, (int(start), 0), (int(end), 50), (r,g,b), -1)
+            start = end
+
+        #display chart
+        plt.figure()
+        plt.axis("off")
+        plt.imshow(chart)
+        plt.show()