Adobe Photoshop-style posterization and OpenCV

Question

It seems Adobe Photoshop does posterization by quantizing each color channel separately, based on the number of levels specified. So for example, if you specify 2 levels, t

Answer 1

Your question specifically seems to be asking about a level of 2. But what about levels more than 2. So i have added a code below which can posterize for any level of color.

import numpy as np
import cv2

im = cv2.imread('messi5.jpg')

n = 2    # Number of levels of quantization

indices = np.arange(0,256)   # List of all colors 

divider = np.linspace(0,255,n+1)[1] # we get a divider

quantiz = np.int0(np.linspace(0,255,n)) # we get quantization colors

color_levels = np.clip(np.int0(indices/divider),0,n-1) # color levels 0,1,2..

palette = quantiz[color_levels] # Creating the palette

im2 = palette[im]  # Applying palette on image

im2 = cv2.convertScaleAbs(im2) # Converting image back to uint8

cv2.imshow('im2',im2)
cv2.waitKey(0)
cv2.destroyAllWindows()

This code uses a method called palette method in Numpy which is really fast than iterating through the pixels. You can find more details how it can be used to speed up code here : Fast Array Manipulation in Numpy

Below are the results I obtained for different levels:

Original Image :

Level 2 :

Level 4 :

Level 8 :

And so on...

Answer 2

We can do this quite neatly using numpy, without having to worry about the channels at all!

import cv2
im = cv2.imread('1_tree_small.jpg')
im[im >= 128]= 255
im[im < 128] = 0
cv2.imwrite('out.jpg', im)

output:

input:

Answer 3

The coolest "posterization" I have seen uses Mean Shift Segmentation. I used the code from the author's GitHub repo to create the following image (you need to uncomment line 27 of Maincpp.cpp to perform the segmentation step).