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Update treatment of convert2lab in slic

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It still defaults to `True` but only when the last dimension of the
input array could be construed as RGB.

Also, update ValueError description in docstring.
This commit is contained in:
Juan Nunez-Iglesias
2015-01-16 13:11:25 +11:00
parent c102a0bf0e
commit 879a7b0bb5
2 changed files with 32 additions and 16 deletions
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skimage/segmentation/tests/test_slic.py
+22 -7
View File
@@ -1,5 +1,4 @@
import itertools as it
import warnings
import numpy as np
from numpy.testing import assert_equal, assert_raises
from skimage.segmentation import slic
@@ -14,9 +13,27 @@ def test_color_2d():
img += 0.01 * rnd.normal(size=img.shape)
img[img > 1] = 1
img[img < 0] = 0
with warnings.catch_warnings():
warnings.simplefilter("ignore")
seg = slic(img, n_segments=4, sigma=0)
seg = slic(img, n_segments=4, sigma=0, enforce_connectivity=False)
# we expect 4 segments
assert_equal(len(np.unique(seg)), 4)
assert_equal(seg.shape, img.shape[:-1])
assert_equal(seg[:10, :10], 0)
assert_equal(seg[10:, :10], 2)
assert_equal(seg[:10, 10:], 1)
assert_equal(seg[10:, 10:], 3)
def test_multichannel_2d():
rnd = np.random.RandomState(0)
img = np.zeros((20, 20, 8))
img[:10, :10, 0:2] = 1
img[:10, 10:, 2:4] = 1
img[10:, :10, 4:6] = 1
img[10:, 10:, 6:8] = 1
img += 0.01 * rnd.normal(size=img.shape)
img = np.clip(img, 0, 1, out=img)
seg = slic(img, n_segments=4, enforce_connectivity=False)
# we expect 4 segments
assert_equal(len(np.unique(seg)), 4)
@@ -158,9 +175,7 @@ def test_slic_zero():
img += 0.01 * rnd.normal(size=img.shape)
img[img > 1] = 1
img[img < 0] = 0
with warnings.catch_warnings():
warnings.simplefilter("ignore")
seg = slic(img, n_segments=4, sigma=0, slic_zero=True)
seg = slic(img, n_segments=4, sigma=0, slic_zero=True)
# we expect 4 segments
assert_equal(len(np.unique(seg)), 4)