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
|
import os.path
import pickle
import shutil
import tempfile
import unittest
import pcl
import numpy as np
# _data = [(i, 2 * i, 3 * i + 0.2) for i in range(500)]
import random
_data = [(random.random(), random.random(), random.random())
for i in range(500)]
# sample_consensus
### RandomSampleConsensus ###
class TestRandomSampleConsensus(unittest.TestCase):
def setUp(self):
self.p = pcl.PointCloud(_data)
# def test_SampleConsensusModel(self):
# model = pcl.SampleConsensusModel(self.p)
# ransac = pcl.RandomSampleConsensus (model)
# ransac.set_DistanceThreshold (.01)
# ransac.computeModel()
# inliers = ransac.get_Inliers()
#
# # print(str(len(inliers)))
# self.assertNotEqual(len(inliers), 0)
# def test_SampleConsensusModelCylinder(self):
# model_cy = pcl.SampleConsensusModelCylinder(self.p)
# ransac = pcl.RandomSampleConsensus (model_cy)
# ransac.set_DistanceThreshold (.01)
# ransac.computeModel()
# inliers = ransac.get_Inliers()
#
# # print(str(len(inliers)))
# self.assertNotEqual(len(inliers), 0)
def test_SampleConsensusModelLine(self):
model_line = pcl.SampleConsensusModelLine(self.p)
ransac = pcl.RandomSampleConsensus(model_line)
ransac.set_DistanceThreshold(.01)
ransac.computeModel()
inliers = ransac.get_Inliers()
# print(str(len(inliers)))
self.assertNotEqual(len(inliers), 0)
def test_ModelPlane(self):
model_p = pcl.SampleConsensusModelPlane(self.p)
ransac = pcl.RandomSampleConsensus(model_p)
ransac.set_DistanceThreshold(.01)
ransac.computeModel()
inliers = ransac.get_Inliers()
# print(str(len(inliers)))
self.assertNotEqual(len(inliers), 0)
final = pcl.PointCloud()
if len(inliers) != 0:
finalpoints = np.zeros((len(inliers), 3), dtype=np.float32)
for i in range(0, len(inliers)):
finalpoints[i][0] = self.p[inliers[i]][0]
finalpoints[i][1] = self.p[inliers[i]][1]
finalpoints[i][2] = self.p[inliers[i]][2]
final.from_array(finalpoints)
self.assertNotEqual(final.size, 0)
pass
# def test_SampleConsensusModelRegistration(self):
# model_reg = pcl.SampleConsensusModelRegistration(self.p)
# ransac = pcl.RandomSampleConsensus (model_reg)
# ransac.set_DistanceThreshold (.01)
# ransac.computeModel()
# inliers = ransac.get_Inliers()
#
# # print(str(len(inliers)))
# self.assertNotEqual(len(inliers), 0)
def test_ModelSphere(self):
model_s = pcl.SampleConsensusModelSphere(self.p)
ransac = pcl.RandomSampleConsensus(model_s)
ransac.set_DistanceThreshold(.01)
ransac.computeModel()
inliers = ransac.get_Inliers()
# print(str(len(inliers)))
self.assertNotEqual(len(inliers), 0)
final = pcl.PointCloud()
if len(inliers) != 0:
finalpoints = np.zeros((len(inliers), 3), dtype=np.float32)
for i in range(0, len(inliers)):
finalpoints[i][0] = self.p[inliers[i]][0]
finalpoints[i][1] = self.p[inliers[i]][1]
finalpoints[i][2] = self.p[inliers[i]][2]
final.from_array(finalpoints)
self.assertNotEqual(final.size, 0)
pass
def test_SampleConsensusModelStick(self):
model_st = pcl.SampleConsensusModelStick(self.p)
ransac = pcl.RandomSampleConsensus(model_st)
ransac.set_DistanceThreshold(.01)
ransac.computeModel()
inliers = ransac.get_Inliers()
# print(str(len(inliers)))
self.assertNotEqual(len(inliers), 0)
# def testException(self):
# self.assertRaises(TypeError, pcl.RandomSampleConsensus)
# pass
def suite():
suite = unittest.TestSuite()
# Sampleconsensus
suite.addTests(unittest.makeSuite(TestRandomSampleConsensus))
return suite
if __name__ == '__main__':
testSuite = suite()
unittest.TextTestRunner().run(testSuite)
|
