OpenCV python, SuperPixel example source code. (usage of createSuperpixelSEEDS)

input image



output image

 
 


source code

import cv2 as cv

import numpy as np

import sys

import random

#read image

img = cv.imread('izone_oy.png')

converted_img = cv.cvtColor(img, cv.COLOR_BGR2HSV)

height,width,channels = converted_img.shape

num_iterations = 6

prior = 2

double_step = False

num_superpixels = 200

num_levels = 4

num_histogram_bins = 5

seeds = cv.ximgproc.createSuperpixelSEEDS(width, height, channels, num_superpixels, num_levels, prior, num_histogram_bins)

color_img = np.zeros((height,width,3), np.uint8)

color_img[:] = (0, 0, 255)

seeds.iterate(converted_img, num_iterations)

# retrieve the segmentation result

labels = seeds.getLabels()

# labels output: use the last x bits to determine the color

num_label_bits = 2

labels &= (1<<num_label_bits)-1

labels *= 1<<(16-num_label_bits)

mask = seeds.getLabelContourMask(False)

# stitch foreground & background together

mask_inv = cv.bitwise_not(mask)

result_bg = cv.bitwise_and(img, img, mask=mask_inv)

result_fg = cv.bitwise_and(color_img, color_img, mask=mask)

result = cv.add(result_bg, result_fg)

cv.namedWindow('mask',0)

cv.namedWindow('result_bg',0)

cv.namedWindow('result_fg',0)

cv.namedWindow('result',0)

cv.imshow('mask',mask_inv)

cv.imshow('result_bg',result_bg)

cv.imshow('result_fg',result_fg)

cv.imshow('result',result)

cv.imwrite('mask.jpg',mask_inv)

cv.imwrite('result_bg.jpg',result_bg)

cv.imwrite('result_fg.jpg',result_fg)

cv.imwrite('result.jpg',result)

cv.waitKey(0)

reference
https://docs.opencv.org/3.0-beta/modules/ximgproc/doc/superpixels.html
https://github.com/opencv/opencv_contrib/blob/master/samples/python2/seeds.py