watershed_sample.py

import matplotlib.pyplot as plt

from skimage.morphology import watershed,disk
from skimage.filter import rank
from skimage import data

import numpy as np

image = data.camera()
gradient = rank.gradient(image, disk(2))
markers = np.zeros(image.shape)
markers[100,150] = 1
markers[200,200] = 2
markers[240,200] = 3
labels = watershed(gradient, markers)

plt.imshow(labels, cmap=plt.cm.spectral, interpolation='nearest')
plt.imshow(markers, interpolation='nearest',alpha = .6)
plt.show()