def test_bimodal_multiotsu_hist():
for name in ['camera', 'moon', 'coins', 'text', 'clock', 'page']:
img = getattr(data, name)()
assert threshold_otsu(img) == threshold_multiotsu(img, 2)
for name in ['chelsea', 'coffee', 'astronaut', 'rocket']:
img = rgb2gray(getattr(data, name)())
assert threshold_otsu(img) == threshold_multiotsu(img, 2)
def test_multiotsu_hist_parameter():
for classes in [2, 3, 4]:
for name in ['camera', 'moon', 'coins', 'text', 'clock', 'page']:
img = getattr(data, name)()
sk_hist = histogram(img, nbins=256)
#
thresh_img = threshold_multiotsu(img, classes)
thresh_sk_hist = threshold_multiotsu(classes=classes, hist=sk_hist)
assert np.allclose(thresh_img, thresh_sk_hist)
def test_multiotsu_output():
image = np.zeros((100, 100), dtype='int')
coords = [(25, 25), (50, 50), (75, 75)]
values = [64, 128, 192]
for coor, val in zip(coords, values):
rr, cc = circle(coor[1], coor[0], 20)
image[rr, cc] = val
thresholds = [64, 128]
assert np.array_equal(thresholds, threshold_multiotsu(image))
image = color.rgb2gray(data.astronaut())
assert_almost_equal(threshold_multiotsu(image, 2), 0.43945312)
def test_check_multiotsu_results():
image = 0.25 * np.array([[0, 1, 2, 3, 4], [0, 1, 2, 3, 4], [0, 1, 2, 3, 4],
[0, 1, 2, 3, 4]])
for idx in range(3, 6):
thr_multi = threshold_multiotsu(image, classes=idx)
assert len(thr_multi) == idx - 1
def test_multiotsu_output():
image = np.zeros((100, 100), dtype='int')
coords = [(25, 25), (50, 50), (75, 75)]
values = [64, 128, 192]
for coor, val in zip(coords, values):
rr, cc = disk(coor, 20)
image[rr, cc] = val
thresholds = [0, 64, 128]
assert np.array_equal(thresholds, threshold_multiotsu(image, classes=4))
def test_multiotsu_output():
image = np.zeros((100, 100), dtype='int')
coords = [(25, 25), (50, 50), (75, 75)]
values = [64, 128, 192]
for coor, val in zip(coords, values):
rr, cc = circle(coor[1], coor[0], 20)
image[rr, cc] = val
t1, t2 = threshold_multiotsu(image)
# since the image only contains values 64, 128, 192, and the image is
# compared to the threshold with a strictly greater than check, thresholds
# 64, 65, ..., 127 are all equivalent, and thresholds 128, 129, ..., 191
# are all equivalent. The overly stringent check of t1 == 64 was causing
# some 32-bit builds to fail. See e.g.
# https://travis-ci.org/scikit-image/scikit-image-wheels/jobs/595911861#L3896-L3911
assert t1 in range(64, 128)
assert t2 in range(128, 192)
image = color.rgb2gray(data.astronaut())
assert_almost_equal(threshold_multiotsu(image, 2), 0.43945312)
def test_multiotsu_more_classes_then_values():
img = np.ones((10, 10), dtype=np.uint8)
with testing.raises(ValueError):
threshold_multiotsu(img, classes=2)
img[:, 3:] = 2
with testing.raises(ValueError):
threshold_multiotsu(img, classes=3)
img[:, 6:] = 3
with testing.raises(ValueError):
threshold_multiotsu(img, classes=4)
def test_multiotsu_astro_image():
img = util.img_as_ubyte(data.astronaut())
with expected_warnings(['grayscale']):
assert_almost_equal(threshold_multiotsu(img), [58, 149])
def test_bimodal_multiotsu_hist():
image = data.camera()
thr_otsu = threshold_otsu(image)
thr_multi = threshold_multiotsu(image, classes=2)
assert thr_otsu == thr_multi
def test_multiotsu_missing_img_and_hist():
with pytest.raises(Exception):
threshold_multiotsu()
