Scikit-Image中傳統分割方法測試

import numpy as np
from skimage.data import astronaut
from skimage.color import rgb2gray
from skimage.filters import sobel
from skimage.segmentation import felzenszwalb, slic, quickshift, watershed
from skimage.segmentation import mark_boundaries
from skimage.util import img_as_float
from skimage import io

img_path = "./sample.jpg"
img = io.imread(img_path)
segments_fz = felzenszwalb(img, scale=100, sigma=0.5, min_size=50)
io.imsave('./3.jpg',segments_fz)
segments_slic = slic(img, n_segments=400, compactness=30, sigma=1)
io.imsave('./4.jpg',segments_slic)
segments_quick = quickshift(img, kernel_size=3, max_dist=6, ratio=0.5)
io.imsave('./5.jpg',segments_quick)
gradient = sobel(rgb2gray(img))
segments_watershed = watershed(gradient, markers=250, compactness=0.001)
io.imsave('./6.jpg',segments_watershed)

3.jpg

4.jpg

5.jpg

6.jpg