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
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
|
# -*- coding: utf-8 -*-
cimport pcl_segmentation_180 as pclseg
cimport pcl_defs as cpp
cimport pcl_sample_consensus_180 as pcl_sc
cimport eigen as eigen3
#yeah, I can't be bothered making this inherit from SACSegmentation, I forget the rules
#for how this works in cython templated extension types anyway
cdef class SegmentationNormal:
"""
Segmentation class for Sample Consensus methods and models that require the
use of surface normals for estimation.
Due to Cython limitations this should derive from pcl.Segmentation, but
is currently unable to do so.
"""
cdef pclseg.SACSegmentationFromNormals_t *me
def __cinit__(self):
self.me = new pclseg.SACSegmentationFromNormals_t()
def __dealloc__(self):
del self.me
def segment(self):
cdef cpp.PointIndices ind
cdef cpp.ModelCoefficients coeffs
self.me.segment (ind, coeffs)
return [ind.indices[i] for i in range(ind.indices.size())],\
[coeffs.values[i] for i in range(coeffs.values.size())]
def set_optimize_coefficients(self, bool b):
self.me.setOptimizeCoefficients(b)
def set_model_type(self, pcl_sc.SacModel m):
self.me.setModelType(m)
def set_method_type(self, int m):
self.me.setMethodType (m)
def set_distance_threshold(self, float d):
self.me.setDistanceThreshold (d)
def set_optimize_coefficients(self, bool b):
self.me.setOptimizeCoefficients (b)
def set_normal_distance_weight(self, float f):
self.me.setNormalDistanceWeight (f)
def set_max_iterations(self, int i):
self.me.setMaxIterations (i)
def set_radius_limits(self, float f1, float f2):
self.me.setRadiusLimits (f1, f2)
def set_eps_angle(self, double ea):
(<pclseg.SACSegmentation_t*>self.me).setEpsAngle (ea)
def get_eps_angle(self):
return (<pclseg.SACSegmentation_PointXYZRGB_t*>self.me).getEpsAngle()
def set_axis(self, double ax1, double ax2, double ax3):
cdef eigen3.Vector3f* vec = new eigen3.Vector3f(ax1, ax2, ax3)
(<pclseg.SACSegmentation_t*>self.me).setAxis(deref(vec))
def get_axis(self):
vec = (<pclseg.SACSegmentation_t*>self.me).getAxis()
cdef float *data = vec.data()
return np.array([data[0], data[1], data[2]], dtype=np.float32)
def set_min_max_opening_angle(self, double min_angle, double max_angle):
"""
Set the minimum and maximum cone opening angles in radians for a cone model.
"""
self.me.setMinMaxOpeningAngle(min_angle, max_angle)
def get_min_max_opening_angle(self):
min_angle = 0.0
max_angle = 0.0
self.me.getMinMaxOpeningAngle(min_angle, max_angle)
return min_angle, max_angle
cdef class Segmentation_PointXYZI_Normal:
"""
Segmentation class for Sample Consensus methods and models that require the
use of surface normals for estimation.
Due to Cython limitations this should derive from pcl.Segmentation, but
is currently unable to do so.
"""
cdef pclseg.SACSegmentationFromNormals_PointXYZI_t *me
def __cinit__(self):
self.me = new pclseg.SACSegmentationFromNormals_PointXYZI_t()
def __dealloc__(self):
del self.me
def segment(self):
cdef cpp.PointIndices ind
cdef cpp.ModelCoefficients coeffs
self.me.segment (ind, coeffs)
return [ind.indices[i] for i in range(ind.indices.size())],\
[coeffs.values[i] for i in range(coeffs.values.size())]
def set_optimize_coefficients(self, bool b):
self.me.setOptimizeCoefficients(b)
def set_model_type(self, pcl_sc.SacModel m):
self.me.setModelType(m)
def set_method_type(self, int m):
self.me.setMethodType (m)
def set_distance_threshold(self, float d):
self.me.setDistanceThreshold (d)
def set_optimize_coefficients(self, bool b):
self.me.setOptimizeCoefficients (b)
def set_normal_distance_weight(self, float f):
self.me.setNormalDistanceWeight (f)
def set_max_iterations(self, int i):
self.me.setMaxIterations (i)
def set_radius_limits(self, float f1, float f2):
self.me.setRadiusLimits (f1, f2)
def set_eps_angle(self, double ea):
self.me.setEpsAngle (ea)
def get_eps_angle(self):
return (<pclseg.SACSegmentation_PointXYZRGB_t*>self.me).getEpsAngle()
def set_axis(self, double ax1, double ax2, double ax3):
cdef eigen3.Vector3f* vec = new eigen3.Vector3f(ax1, ax2, ax3)
(<pclseg.SACSegmentation_PointXYZI_t*>self.me).setAxis(deref(vec))
def get_axis(self):
vec = (<pclseg.SACSegmentation_t*>self.me).getAxis()
cdef float *data = vec.data()
return np.array([data[0], data[1], data[2]], dtype=np.float32)
def set_min_max_opening_angle(self, double min_angle, double max_angle):
"""
Set the minimum and maximum cone opening angles in radians for a cone model.
"""
self.me.setMinMaxOpeningAngle(min_angle, max_angle)
def get_min_max_opening_angle(self):
min_angle = 0.0
max_angle = 0.0
self.me.getMinMaxOpeningAngle(min_angle, max_angle)
return min_angle, max_angle
cdef class Segmentation_PointXYZRGB_Normal:
"""
Segmentation class for Sample Consensus methods and models that require the
use of surface normals for estimation.
Due to Cython limitations this should derive from pcl.Segmentation, but
is currently unable to do so.
"""
cdef pclseg.SACSegmentationFromNormals_PointXYZRGB_t *me
def __cinit__(self):
self.me = new pclseg.SACSegmentationFromNormals_PointXYZRGB_t()
def __dealloc__(self):
del self.me
def segment(self):
cdef cpp.PointIndices ind
cdef cpp.ModelCoefficients coeffs
self.me.segment (ind, coeffs)
return [ind.indices[i] for i in range(ind.indices.size())],\
[coeffs.values[i] for i in range(coeffs.values.size())]
def set_optimize_coefficients(self, bool b):
self.me.setOptimizeCoefficients(b)
def set_model_type(self, pcl_sc.SacModel m):
self.me.setModelType(m)
def set_method_type(self, int m):
self.me.setMethodType (m)
def set_distance_threshold(self, float d):
self.me.setDistanceThreshold (d)
def set_optimize_coefficients(self, bool b):
self.me.setOptimizeCoefficients (b)
def set_normal_distance_weight(self, float f):
self.me.setNormalDistanceWeight (f)
def set_max_iterations(self, int i):
self.me.setMaxIterations (i)
def set_radius_limits(self, float f1, float f2):
self.me.setRadiusLimits (f1, f2)
def set_eps_angle(self, double ea):
self.me.setEpsAngle (ea)
def get_eps_angle(self):
return (<pclseg.SACSegmentation_PointXYZRGB_t*>self.me).getEpsAngle()
def set_axis(self, double ax1, double ax2, double ax3):
cdef eigen3.Vector3f* vec = new eigen3.Vector3f(ax1, ax2, ax3)
(<pclseg.SACSegmentation_PointXYZRGB_t*>self.me).setAxis(deref(vec))
def get_axis(self):
vec = (<pclseg.SACSegmentation_t*>self.me).getAxis()
cdef float *data = vec.data()
return np.array([data[0], data[1], data[2]], dtype=np.float32)
def set_min_max_opening_angle(self, double min_angle, double max_angle):
"""
Set the minimum and maximum cone opening angles in radians for a cone model.
"""
self.me.setMinMaxOpeningAngle(min_angle, max_angle)
def get_min_max_opening_angle(self):
min_angle = 0.0
max_angle = 0.0
self.me.getMinMaxOpeningAngle(min_angle, max_angle)
return min_angle, max_angle
cdef class Segmentation_PointXYZRGBA_Normal:
"""
Segmentation class for Sample Consensus methods and models that require the
use of surface normals for estimation.
Due to Cython limitations this should derive from pcl.Segmentation, but
is currently unable to do so.
"""
cdef pclseg.SACSegmentationFromNormals_PointXYZRGBA_t *me
def __cinit__(self):
self.me = new pclseg.SACSegmentationFromNormals_PointXYZRGBA_t()
def __dealloc__(self):
del self.me
def segment(self):
cdef cpp.PointIndices ind
cdef cpp.ModelCoefficients coeffs
self.me.segment (ind, coeffs)
return [ind.indices[i] for i in range(ind.indices.size())],\
[coeffs.values[i] for i in range(coeffs.values.size())]
def set_optimize_coefficients(self, bool b):
self.me.setOptimizeCoefficients(b)
def set_model_type(self, pcl_sc.SacModel m):
self.me.setModelType(m)
def set_method_type(self, int m):
self.me.setMethodType (m)
def set_distance_threshold(self, float d):
self.me.setDistanceThreshold (d)
def set_optimize_coefficients(self, bool b):
self.me.setOptimizeCoefficients (b)
def set_normal_distance_weight(self, float f):
self.me.setNormalDistanceWeight (f)
def set_max_iterations(self, int i):
self.me.setMaxIterations (i)
def set_radius_limits(self, float f1, float f2):
self.me.setRadiusLimits (f1, f2)
def set_eps_angle(self, double ea):
vec = (<pclseg.SACSegmentation_PointXYZRGBA_t*>self.me).setEpsAngle(ea)
def get_eps_angle(self):
return (<pclseg.SACSegmentation_PointXYZRGBA_t*>self.me).getEpsAngle()
def set_axis(self, double ax1, double ax2, double ax3):
cdef eigen3.Vector3f* vec = new eigen3.Vector3f(ax1, ax2, ax3)
(<pclseg.SACSegmentation_PointXYZRGBA_t*>self.me).setAxis(deref(vec))
def get_axis(self):
vec = (<pclseg.SACSegmentation_PointXYZRGBA_t*>self.me).getAxis()
cdef float *data = vec.data()
return np.array([data[0], data[1], data[2]], dtype=np.float32)
def set_min_max_opening_angle(self, double min_angle, double max_angle):
"""
Set the minimum and maximum cone opening angles in radians for a cone model.
"""
self.me.setMinMaxOpeningAngle(min_angle, max_angle)
def get_min_max_opening_angle(self):
min_angle = 0.0
max_angle = 0.0
self.me.getMinMaxOpeningAngle(min_angle, max_angle)
return min_angle, max_angle
|
