forked from pmneila/morphsnakes
-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathtest_morphsnakes.py
154 lines (106 loc) · 5.14 KB
/
test_morphsnakes.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
import numpy as np
from morphsnakes import (morphological_chan_vese,
morphological_geodesic_active_contour,
inverse_gaussian_gradient,
circle_level_set, checkerboard_level_set)
from numpy.testing import assert_array_equal
import pytest
def gaussian_blob():
coords = np.mgrid[-5:6, -5:6]
sqrdistances = (coords ** 2).sum(0)
return np.exp(-sqrdistances / 10)
def test_morphsnakes_incorrect_image_shape():
img = np.zeros((10, 10, 3))
ls = np.zeros((10, 9))
with pytest.raises(ValueError):
morphological_chan_vese(img, iterations=1, init_level_set=ls)
with pytest.raises(ValueError):
morphological_geodesic_active_contour(img, iterations=1,
init_level_set=ls)
def test_morphsnakes_incorrect_ndim():
img = np.zeros((4, 4, 4, 4))
ls = np.zeros((4, 4, 4, 4))
with pytest.raises(ValueError):
morphological_chan_vese(img, iterations=1, init_level_set=ls)
with pytest.raises(ValueError):
morphological_geodesic_active_contour(img, iterations=1,
init_level_set=ls)
def test_morphsnakes_black():
img = np.zeros((11, 11))
ls = circle_level_set(img.shape, (5, 5), 3)
ref_zeros = np.zeros(img.shape, dtype=np.int8)
ref_ones = np.ones(img.shape, dtype=np.int8)
acwe_ls = morphological_chan_vese(img, iterations=6, init_level_set=ls)
assert_array_equal(acwe_ls, ref_zeros)
gac_ls = morphological_geodesic_active_contour(img, iterations=6,
init_level_set=ls)
assert_array_equal(gac_ls, ref_zeros)
gac_ls2 = morphological_geodesic_active_contour(img, iterations=6,
init_level_set=ls,
balloon=1, threshold=-1,
smoothing=0)
assert_array_equal(gac_ls2, ref_ones)
assert acwe_ls.dtype == gac_ls.dtype == gac_ls2.dtype == np.int8
def test_morphsnakes_simple_shape_chan_vese():
img = gaussian_blob()
ls1 = circle_level_set(img.shape, (5, 5), 3)
ls2 = circle_level_set(img.shape, (5, 5), 6)
acwe_ls1 = morphological_chan_vese(img, iterations=10, init_level_set=ls1)
acwe_ls2 = morphological_chan_vese(img, iterations=10, init_level_set=ls2)
assert_array_equal(acwe_ls1, acwe_ls2)
assert acwe_ls1.dtype == acwe_ls2.dtype == np.int8
def test_morphsnakes_simple_shape_geodesic_active_contour():
img = np.float_(circle_level_set((11, 11), (5, 5), 3.5))
gimg = inverse_gaussian_gradient(img, alpha=10.0, sigma=1.0)
ls = circle_level_set(img.shape, (5, 5), 6)
ref = 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, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 1, 1, 1, 1, 1, 0, 0, 0],
[0, 0, 0, 1, 1, 1, 1, 1, 0, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 0, 1, 1, 1, 1, 1, 0, 0, 0],
[0, 0, 0, 1, 1, 1, 1, 1, 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]],
dtype=np.int8)
gac_ls = morphological_geodesic_active_contour(gimg, iterations=10,
init_level_set=ls,
balloon=-1)
assert_array_equal(gac_ls, ref)
assert gac_ls.dtype == np.int8
def test_init_level_sets():
image = np.zeros((6, 6))
checkerboard_ls = morphological_chan_vese(image, 0, 'checkerboard')
checkerboard_ref = np.array([[0, 0, 0, 0, 0, 1],
[0, 0, 0, 0, 0, 1],
[0, 0, 0, 0, 0, 1],
[0, 0, 0, 0, 0, 1],
[0, 0, 0, 0, 0, 1],
[1, 1, 1, 1, 1, 0]], dtype=np.int8)
circle_ls = morphological_geodesic_active_contour(image, 0, 'circle')
circle_ref = np.array([[0, 0, 0, 0, 0, 0],
[0, 0, 1, 1, 1, 0],
[0, 1, 1, 1, 1, 1],
[0, 1, 1, 1, 1, 1],
[0, 1, 1, 1, 1, 1],
[0, 0, 1, 1, 1, 0]], dtype=np.int8)
assert_array_equal(checkerboard_ls, checkerboard_ref)
assert_array_equal(circle_ls, circle_ref)
def test_morphsnakes_3d():
image = np.zeros((7, 7, 7))
evolution = []
def callback(x):
evolution.append(x.sum())
ls = morphological_chan_vese(image, 5, 'circle',
iter_callback=callback)
# Check that the initial circle level set is correct
assert evolution[0] == 81
# Check that the final level set is correct
assert ls.sum() == 0
# Check that the contour is shrinking at every iteration
for v1, v2 in zip(evolution[:-1], evolution[1:]):
assert v1 >= v2
if __name__ == "__main__":
np.testing.run_module_suite()