07. Segmentation

This example shows the interface usage for class-based segmentation of a 2D image. First, depending on the size of the weighting lambda, a piecewise constant image is generated before the assignment to certain classes is done.

TV based segmentation

import skimage.data as skd
import numpy as np
import matplotlib.pyplot as plt

from recon.interfaces import Segmentation


def rgb2gray(rgb):
    r, g, b = rgb[:, :, 0], rgb[:, :, 1], rgb[:, :, 2]
    gray = 0.2989 * r + 0.5870 * g + 0.1140 * b
    return gray


gt = rgb2gray(skd.coffee())[:, 80:481]
gt = gt/np.max(gt)
gt = gt/np.max(gt)

classes = [0, 50/255, 120/255, 190/255, 220/255]

segmentation = Segmentation(gt.shape, classes=classes, lam=5, tau='calc')
result, _ = segmentation.solve(gt, max_iter=4000)

f = plt.figure(figsize=(8, 4))
f.add_subplot(1, 2, 1)
plt.axis('off')
plt.imshow(gt)
plt.title("GT")
f.add_subplot(1, 2, 2)
plt.imshow(result)
plt.title("TV-based segmentation")
plt.axis('off')
plt.show(block=False)

Out:

Early stopping.