Posturizing grayscale image using OpenCV-Python

Question

I was trying to posterize an image in python using opencv, after some time of searching i found a lead in openCV documentations . But as you can see its for rgb image and what I've got is a gray-scale image, i did it anyways and got weird outputs. i tweaked some places in the code and got even weirder outputs. Can someone please explain whats going on ?

EDIT:

My code

import numpy as np
import cv2

img = cv2.imread('Lenna.png')
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

Z = np.float32(gray)

criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 10, 1.0)
K = 8
ret,label,center=cv2.kmeans(Z,K,None,criteria,10,cv2.KMEANS_RANDOM_CENTERS)

center = np.uint8(center)
res = center[label.flatten()]

cv2.imshow('res',res)
cv2.waitKey(0)
cv2.destroyAllWindows()

Input image:

Output Image:

Answer 1

Can someone please explain whats going on ?

Kmeans input is a vector of vectors, or in a lot of cases, a vector of pixels or vector of 2D/3D points. In your code you are passing an image, which is a vector of the values in a row. That is why you get this weird values.

What can you do?

Simple, reshape the input to be a 1D vector of grey values.

Z = img.reshape((-1,1))

This way, it will try to use each grey value as input to cluster them (group them) and then it will label each value accordingly.

Answer 2

If you look a bit further in the examples, you can find a solution like this:

import numpy as np
import cv2

img = cv2.imread('Lenna.png')

Z = img.reshape((-1,3))

# convert to np.float32
Z = np.float32(Z)

# define criteria, number of clusters(K) and apply kmeans()
criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 10, 1.0)
K = 8


ret,label,center=cv2.kmeans(Z,K,None,criteria,10,cv2.KMEANS_RANDOM_CENTERS)

# Now convert back into uint8, and make original image
center = np.uint8(center)
res = center[label.flatten()]
res2 = res.reshape((img.shape))

cv2.imshow('res2',res2)
cv2.waitKey(0)
cv2.destroyAllWindows()

Note here the reshape to account for the RGB image.