本文整理汇总了Python中skimage.morphology.watershed.watershed函数的典型用法代码示例。如果您正苦于以下问题：Python watershed函数的具体用法？Python watershed怎么用？Python watershed使用的例子？那么恭喜您, 这里精选的函数代码示例或许可以为您提供帮助。
在下文中一共展示了watershed函数的15个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: test_watershed06
def test_watershed06(self):
"watershed 6"
data = np.array([[0, 1, 0, 0, 0, 1, 0],
[0, 1, 0, 0, 0, 1, 0],
[0, 1, 0, 0, 0, 1, 0],
[0, 1, 1, 1, 1, 1, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0]], np.uint8)
markers = np.array([[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 1, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[-1, 0, 0, 0, 0, 0, 0]], np.int8)
out = watershed(data, markers, self.eight)
error = diff([[-1, 1, 1, 1, 1, 1, -1],
[-1, 1, 1, 1, 1, 1, -1],
[-1, 1, 1, 1, 1, 1, -1],
[-1, 1, 1, 1, 1, 1, -1],
[-1, -1, -1, -1, -1, -1, -1],
[-1, -1, -1, -1, -1, -1, -1],
[-1, -1, -1, -1, -1, -1, -1],
[-1, -1, -1, -1, -1, -1, -1],
[-1, -1, -1, -1, -1, -1, -1]], out)
self.failUnless(error < eps)示例2: test_watershed03
def test_watershed03(self):
"watershed 3"
data = np.array([[0, 0, 0, 0, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0],
[0, 1, 0, 1, 0, 1, 0],
[0, 1, 0, 1, 0, 1, 0],
[0, 1, 0, 1, 0, 1, 0],
[0, 1, 1, 1, 1, 1, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0]], np.uint8)
markers = np.array([[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 2, 0, 3, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, -1]], np.int8)
out = watershed(data, markers)
error = diff([[-1, -1, -1, -1, -1, -1, -1],
[-1, 0, 2, 0, 3, 0, -1],
[-1, 2, 2, 0, 3, 3, -1],
[-1, 2, 2, 0, 3, 3, -1],
[-1, 2, 2, 0, 3, 3, -1],
[-1, 0, 2, 0, 3, 0, -1],
[-1, -1, -1, -1, -1, -1, -1],
[-1, -1, -1, -1, -1, -1, -1],
[-1, -1, -1, -1, -1, -1, -1],
[-1, -1, -1, -1, -1, -1, -1]], out)
self.failUnless(error < eps)示例3: test_watershed05
def test_watershed05(self):
"watershed 5"
data = np.array([[0, 0, 0, 0, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0],
[0, 1, 0, 1, 0, 1, 0],
[0, 1, 0, 1, 0, 1, 0],
[0, 1, 0, 1, 0, 1, 0],
[0, 1, 1, 1, 1, 1, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0]], np.uint8)
markers = np.array([[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 3, 0, 2, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, -1]], np.int8)
out = watershed(data, markers, self.eight)
error = diff([[-1, -1, -1, -1, -1, -1, -1],
[-1, 3, 3, 0, 2, 2, -1],
[-1, 3, 3, 0, 2, 2, -1],
[-1, 3, 3, 0, 2, 2, -1],
[-1, 3, 3, 0, 2, 2, -1],
[-1, 3, 3, 0, 2, 2, -1],
[-1, -1, -1, -1, -1, -1, -1],
[-1, -1, -1, -1, -1, -1, -1],
[-1, -1, -1, -1, -1, -1, -1],
[-1, -1, -1, -1, -1, -1, -1]], out)
self.assertTrue(error < eps)示例4: test_watershed07
def test_watershed07(self):
"A regression test of a competitive case that failed"
data = np.array([[255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255],
[255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255],
[255,255,255,255,255,204,204,204,204,204,204,255,255,255,255,255],
[255,255,255,204,204,183,153,153,153,153,183,204,204,255,255,255],
[255,255,204,183,153,141,111,103,103,111,141,153,183,204,255,255],
[255,255,204,153,111, 94, 72, 52, 52, 72, 94,111,153,204,255,255],
[255,255,204,153,111, 72, 39, 1, 1, 39, 72,111,153,204,255,255],
[255,255,204,183,141,111, 72, 39, 39, 72,111,141,183,204,255,255],
[255,255,255,204,183,141,111, 72, 72,111,141,183,204,255,255,255],
[255,255,255,255,204,183,141, 94, 94,141,183,204,255,255,255,255],
[255,255,255,255,255,204,153,103,103,153,204,255,255,255,255,255],
[255,255,255,255,204,183,141, 94, 94,141,183,204,255,255,255,255],
[255,255,255,204,183,141,111, 72, 72,111,141,183,204,255,255,255],
[255,255,204,183,141,111, 72, 39, 39, 72,111,141,183,204,255,255],
[255,255,204,153,111, 72, 39, 1, 1, 39, 72,111,153,204,255,255],
[255,255,204,153,111, 94, 72, 52, 52, 72, 94,111,153,204,255,255],
[255,255,204,183,153,141,111,103,103,111,141,153,183,204,255,255],
[255,255,255,204,204,183,153,153,153,153,183,204,204,255,255,255],
[255,255,255,255,255,204,204,204,204,204,204,255,255,255,255,255],
[255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255],
[255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255]])
mask = (data != 255)
markers = np.zeros(data.shape, int)
markers[6, 7] = 1
markers[14, 7] = 2
out = watershed(data, markers, self.eight, mask=mask)
#
# The two objects should be the same size, except possibly for the
# border region
#
size1 = np.sum(out == 1)
size2 = np.sum(out == 2)
self.assertTrue(abs(size1 - size2) <= 6)示例5: test_watershed08
def test_watershed08(self):
"The border pixels + an edge are all the same value"
data = np.array([[255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255],
[255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255],
[255,255,255,255,255,204,204,204,204,204,204,255,255,255,255,255],
[255,255,255,204,204,183,153,153,153,153,183,204,204,255,255,255],
[255,255,204,183,153,141,111,103,103,111,141,153,183,204,255,255],
[255,255,204,153,111, 94, 72, 52, 52, 72, 94,111,153,204,255,255],
[255,255,204,153,111, 72, 39, 1, 1, 39, 72,111,153,204,255,255],
[255,255,204,183,141,111, 72, 39, 39, 72,111,141,183,204,255,255],
[255,255,255,204,183,141,111, 72, 72,111,141,183,204,255,255,255],
[255,255,255,255,204,183,141, 94, 94,141,183,204,255,255,255,255],
[255,255,255,255,255,204,153,141,141,153,204,255,255,255,255,255],
[255,255,255,255,204,183,141, 94, 94,141,183,204,255,255,255,255],
[255,255,255,204,183,141,111, 72, 72,111,141,183,204,255,255,255],
[255,255,204,183,141,111, 72, 39, 39, 72,111,141,183,204,255,255],
[255,255,204,153,111, 72, 39, 1, 1, 39, 72,111,153,204,255,255],
[255,255,204,153,111, 94, 72, 52, 52, 72, 94,111,153,204,255,255],
[255,255,204,183,153,141,111,103,103,111,141,153,183,204,255,255],
[255,255,255,204,204,183,153,153,153,153,183,204,204,255,255,255],
[255,255,255,255,255,204,204,204,204,204,204,255,255,255,255,255],
[255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255],
[255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255]])
mask = (data != 255)
markers = np.zeros(data.shape, int)
markers[6, 7] = 1
markers[14, 7] = 2
out = watershed(data, markers, self.eight, mask=mask)
#
# The two objects should be the same size, except possibly for the
# border region
#
size1 = np.sum(out == 1)
size2 = np.sum(out == 2)
self.assertTrue(abs(size1 - size2) <= 6)示例6: test_compact_watershed
def test_compact_watershed():
image = np.zeros((5, 6))
image[:, 3:] = 1
seeds = np.zeros((5, 6), dtype=int)
seeds[2, 0] = 1
seeds[2, 3] = 2
compact = watershed(image, seeds, compactness=0.01)
expected = np.array([[1, 1, 1, 2, 2, 2],
[1, 1, 1, 2, 2, 2],
[1, 1, 1, 2, 2, 2],
[1, 1, 1, 2, 2, 2],
[1, 1, 1, 2, 2, 2]], dtype=int)
np.testing.assert_equal(compact, expected)
normal = watershed(image, seeds)
expected = np.ones(image.shape, dtype=int)
expected[2, 3:] = 2
np.testing.assert_equal(normal, expected)示例7: test_watershed09
def test_watershed09(self):
"""Test on an image of reasonable size
This is here both for timing (does it take forever?) and to
ensure that the memory constraints are reasonable
"""
image = np.zeros((1000, 1000))
coords = np.random.uniform(0, 1000, (100, 2)).astype(int)
markers = np.zeros((1000, 1000), int)
idx = 1
for x, y in coords:
image[x, y] = 1
markers[x, y] = idx
idx += 1
image = ndi.gaussian_filter(image, 4)
watershed(image, markers, self.eight)
ndi.watershed_ift(image.astype(np.uint16), markers, self.eight)示例8: test_numeric_seed_watershed
def test_numeric_seed_watershed():
"""Test that passing just the number of seeds to watershed works."""
image = np.zeros((5, 6))
image[:, 3:] = 1
compact = watershed(image, 2, compactness=0.01)
expected = np.array([[1, 1, 1, 1, 2, 2],
[1, 1, 1, 1, 2, 2],
[1, 1, 1, 1, 2, 2],
[1, 1, 1, 1, 2, 2],
[1, 1, 1, 1, 2, 2]], dtype=np.int32)
np.testing.assert_equal(compact, expected)示例9: test_watershed01
def test_watershed01(self):
"watershed 1"
data = np.array(
[
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0],
[0, 1, 0, 0, 0, 1, 0],
[0, 1, 0, 0, 0, 1, 0],
[0, 1, 0, 0, 0, 1, 0],
[0, 1, 1, 1, 1, 1, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
],
np.uint8,
)
markers = np.array(
[
[-1, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 1, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
],
np.int8,
)
out = watershed(data, markers, self.eight)
expected = np.array(
[
[-1, -1, -1, -1, -1, -1, -1],
[-1, -1, -1, -1, -1, -1, -1],
[-1, -1, -1, -1, -1, -1, -1],
[-1, 1, 1, 1, 1, 1, -1],
[-1, 1, 1, 1, 1, 1, -1],
[-1, 1, 1, 1, 1, 1, -1],
[-1, 1, 1, 1, 1, 1, -1],
[-1, 1, 1, 1, 1, 1, -1],
[-1, -1, -1, -1, -1, -1, -1],
[-1, -1, -1, -1, -1, -1, -1],
]
)
error = diff(expected, out)
assert error < eps
out = _slow_watershed(data, markers, 8)
error = diff(expected, out)
assert error < eps示例10: test_watershed02
def test_watershed02(self):
"watershed 2"
data = np.array(
[
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0],
[0, 1, 0, 0, 0, 1, 0],
[0, 1, 0, 0, 0, 1, 0],
[0, 1, 0, 0, 0, 1, 0],
[0, 1, 1, 1, 1, 1, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
],
np.uint8,
)
markers = np.array(
[
[-1, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 1, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
],
np.int8,
)
out = watershed(data, markers)
error = diff(
[
[-1, -1, -1, -1, -1, -1, -1],
[-1, -1, -1, -1, -1, -1, -1],
[-1, -1, -1, -1, -1, -1, -1],
[-1, -1, -1, -1, -1, -1, -1],
[-1, -1, 1, 1, 1, -1, -1],
[-1, 1, 1, 1, 1, 1, -1],
[-1, 1, 1, 1, 1, 1, -1],
[-1, 1, 1, 1, 1, 1, -1],
[-1, -1, 1, 1, 1, -1, -1],
[-1, -1, -1, -1, -1, -1, -1],
[-1, -1, -1, -1, -1, -1, -1],
],
out,
)
self.failUnless(error < eps)示例11: test_watershed05
def test_watershed05(self):
"watershed 5"
data = np.array(
[
[0, 0, 0, 0, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0],
[0, 1, 0, 1, 0, 1, 0],
[0, 1, 0, 1, 0, 1, 0],
[0, 1, 0, 1, 0, 1, 0],
[0, 1, 1, 1, 1, 1, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
],
np.uint8,
)
markers = np.array(
[
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 3, 0, 2, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, -1],
],
np.int8,
)
out = watershed(data, markers, self.eight)
error = diff(
[
[-1, -1, -1, -1, -1, -1, -1],
[-1, 3, 3, 0, 2, 2, -1],
[-1, 3, 3, 0, 2, 2, -1],
[-1, 3, 3, 0, 2, 2, -1],
[-1, 3, 3, 0, 2, 2, -1],
[-1, 3, 3, 0, 2, 2, -1],
[-1, -1, -1, -1, -1, -1, -1],
[-1, -1, -1, -1, -1, -1, -1],
[-1, -1, -1, -1, -1, -1, -1],
[-1, -1, -1, -1, -1, -1, -1],
],
out,
)
self.failUnless(error < eps)示例12: test_watershed07
def test_watershed07(self):
"A regression test of a competitive case that failed"
data = blob
mask = (data != 255)
markers = np.zeros(data.shape, int)
markers[6, 7] = 1
markers[14, 7] = 2
out = watershed(data, markers, self.eight, mask=mask)
#
# The two objects should be the same size, except possibly for the
# border region
#
size1 = np.sum(out == 1)
size2 = np.sum(out == 2)
self.assertTrue(abs(size1 - size2) <= 6)示例13: test_watershed08
def test_watershed08(self):
"The border pixels + an edge are all the same value"
data = blob.copy()
data[10, 7:9] = 141
mask = (data != 255)
markers = np.zeros(data.shape, int)
markers[6, 7] = 1
markers[14, 7] = 2
out = watershed(data, markers, self.eight, mask=mask)
#
# The two objects should be the same size, except possibly for the
# border region
#
size1 = np.sum(out == 1)
size2 = np.sum(out == 2)
self.assertTrue(abs(size1 - size2) <= 6)示例14: test_watershed10
def test_watershed10(self):
"watershed 10"
data = np.array([[1, 1, 1, 1],
[1, 1, 1, 1],
[1, 1, 1, 1],
[1, 1, 1, 1]], np.uint8)
markers = np.array([[1, 0, 0, 2],
[0, 0, 0, 0],
[0, 0, 0, 0],
[3, 0, 0, 4]], np.int8)
out = watershed(data, markers, self.eight)
error = diff([[1, 1, 2, 2],
[1, 1, 2, 2],
[3, 3, 4, 4],
[3, 3, 4, 4]], out)
self.assertTrue(error < eps)示例15: test_watershed12
def test_watershed12(self):
"The watershed line"
data = np.array([[203, 255, 203, 153, 153, 153, 153, 153, 153, 153, 153, 153, 153, 153, 153, 153],
[203, 255, 203, 153, 153, 153, 102, 102, 102, 102, 102, 102, 153, 153, 153, 153],
[203, 255, 203, 203, 153, 153, 102, 102, 77, 0, 102, 102, 153, 153, 203, 203],
[203, 255, 255, 203, 153, 153, 153, 102, 102, 102, 102, 153, 153, 203, 203, 255],
[203, 203, 255, 203, 203, 203, 153, 153, 153, 153, 153, 153, 203, 203, 255, 255],
[153, 203, 255, 255, 255, 203, 203, 203, 203, 203, 203, 203, 203, 255, 255, 203],
[153, 203, 203, 203, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 203, 203],
[153, 153, 153, 203, 203, 203, 203, 203, 255, 203, 203, 203, 203, 203, 203, 153],
[102, 102, 153, 153, 153, 153, 203, 203, 255, 203, 203, 255, 203, 153, 153, 153],
[102, 102, 102, 102, 102, 153, 203, 255, 255, 203, 203, 203, 203, 153, 102, 153],
[102, 51, 51, 102, 102, 153, 203, 255, 203, 203, 153, 153, 153, 153, 102, 153],
[ 77, 51, 51, 102, 153, 153, 203, 255, 203, 203, 203, 153, 102, 102, 102, 153],
[ 77, 0, 51, 102, 153, 203, 203, 255, 203, 255, 203, 153, 102, 51, 102, 153],
[ 77, 0, 51, 102, 153, 203, 255, 255, 203, 203, 203, 153, 102, 0, 102, 153],
[102, 0, 51, 102, 153, 203, 255, 203, 203, 153, 153, 153, 102, 102, 102, 153],
[102, 102, 102, 102, 153, 203, 255, 203, 153, 153, 153, 153, 153, 153, 153, 153]])
markerbin = (data==0)
marker = label(markerbin)
ws = watershed(data, marker, connectivity=2, watershed_line=True)
for lab, area in zip(range(4), [34,74,74,74]):
self.assertTrue(np.sum(ws == lab) == area)