CofeehousePy/deps/scikit-image/skimage/segmentation/tests/test_quickshift.py

50 lines
1.7 KiB
Python

import numpy as np
from skimage.segmentation import quickshift
from skimage._shared.testing import (assert_greater, test_parallel,
assert_equal, assert_array_equal)
@test_parallel()
def test_grey():
rnd = np.random.RandomState(0)
img = np.zeros((20, 21))
img[:10, 10:] = 0.2
img[10:, :10] = 0.4
img[10:, 10:] = 0.6
img += 0.1 * rnd.normal(size=img.shape)
seg = quickshift(img, kernel_size=2, max_dist=3, random_seed=0,
convert2lab=False, sigma=0)
# we expect 4 segments:
assert_equal(len(np.unique(seg)), 4)
# that mostly respect the 4 regions:
for i in range(4):
hist = np.histogram(img[seg == i], bins=[0, 0.1, 0.3, 0.5, 1])[0]
assert_greater(hist[i], 20)
def test_color():
rnd = np.random.RandomState(0)
img = np.zeros((20, 21, 3))
img[:10, :10, 0] = 1
img[10:, :10, 1] = 1
img[10:, 10:, 2] = 1
img += 0.01 * rnd.normal(size=img.shape)
img[img > 1] = 1
img[img < 0] = 0
seg = quickshift(img, random_seed=0, max_dist=30, kernel_size=10, sigma=0)
# we expect 4 segments:
assert_equal(len(np.unique(seg)), 4)
assert_array_equal(seg[:10, :10], 1)
assert_array_equal(seg[10:, :10], 2)
assert_array_equal(seg[:10, 10:], 0)
assert_array_equal(seg[10:, 10:], 3)
seg2 = quickshift(img, kernel_size=1, max_dist=2, random_seed=0,
convert2lab=False, sigma=0)
# very oversegmented:
assert_equal(len(np.unique(seg2)), 7)
# still don't cross lines
assert (seg2[9, :] != seg2[10, :]).all()
assert (seg2[:, 9] != seg2[:, 10]).all()