Usage example for `aexpansion_grid` from PyMaxflow

aexpansion_example.py

import numpy as np
import matplotlib.pyplot as plt
import imageio

from maxflow.fastmin import aexpansion_grid

# Loading image
I = imageio.imread('imageio:astronaut.png')
I = I[:,:,1]/I.max()

# Generates 16 gray levels for nearsest prototype labeling
L = 16
levs = np.arange(0.5/L, 1, 1/L)

# Calculate data cost as the absolute difference between the label prototype and the pixel value
D = np.abs(I.reshape(I.shape+(1,)) - levs.reshape((1,1,-1)))

# Generate nearest prototype labeling
Id = np.argmin(D,2)

fg = plt.figure("Direct labeling")
ax1 = fg.add_subplot(1,1,1)
ax1.imshow(Id)

# Calculate neighbourhood cost as absolute difference between prototypes 
alpha = 1
V = alpha * np.abs( levs.reshape((-1,1)) - levs.reshape((1,-1)))

# Mimimise data + neighbourhood cost
labels = aexpansion_grid(D,V)

fg = plt.figure("Regularised labeling")
ax1 = fg.add_subplot(1,1,1)
ax1.imshow(labels)