ENH tests for Felzenszwalbs segmentation, fixed off-by-one error

This commit is contained in:
Andreas Mueller
2012-08-03 11:37:11 +01:00
parent a7c98cb67a
commit d2e226fe59
2 changed files with 41 additions and 2 deletions
@@ -0,0 +1,39 @@
import numpy as np
from numpy.testing import assert_equal, assert_array_equal
from nose.tools import assert_greater
from skimage.segmentation import felzenszwalb_segmentation
def test_grey():
# very weak tests. This algorithm is pretty unstable.
img = np.zeros((20, 20))
img[:10, 10:] = 0.2
img[10:, :10] = 0.4
img[10:, 10:] = 0.6
seg = felzenszwalb_segmentation(img, sigma=0)
# we expect 4 segments:
assert_equal(len(np.unique(seg)), 4)
# that mostly respect the 4 regions:
for i in xrange(4):
hist = np.histogram(img[seg == i], bins=[0, 0.1, 0.3, 0.5, 1])[0]
assert_greater(hist[i], 40)
def test_color():
# very weak tests. This algorithm is pretty unstable.
img = np.zeros((20, 20, 3))
img[:10, :10, 0] = 1
img[10:, :10, 1] = 1
img[10:, 10:, 2] = 1
seg = felzenszwalb_segmentation(img, sigma=0)
# we expect 4 segments:
assert_equal(len(np.unique(seg)), 4)
assert_array_equal(seg[:10, :10], 0)
assert_array_equal(seg[10:, :10], 3)
assert_array_equal(seg[:10, 10:], 1)
assert_array_equal(seg[10:, 10:], 2)
if __name__ == '__main__':
from numpy import testing
testing.run_module_suite()