forked from HuguesTHOMAS/KPConv-PyTorch
-
Notifications
You must be signed in to change notification settings - Fork 0
/
mayavi_visu.py
436 lines (320 loc) · 12.1 KB
/
mayavi_visu.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
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
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
#
#
# 0=================================0
# | Kernel Point Convolutions |
# 0=================================0
#
#
# ----------------------------------------------------------------------------------------------------------------------
#
# Script for various visualization with mayavi
#
# ----------------------------------------------------------------------------------------------------------------------
#
# Hugues THOMAS - 11/06/2018
#
# ----------------------------------------------------------------------------------------------------------------------
#
# Imports and global variables
# \**********************************/
#
# Basic libs
import torch
import numpy as np
from sklearn.neighbors import KDTree
from os import makedirs, remove, rename, listdir
from os.path import exists, join
import time
import sys
# PLY reader
from utils.ply import write_ply, read_ply
# Configuration class
from utils.config import Config
def show_ModelNet_models(all_points):
from mayavi import mlab
###########################
# Interactive visualization
###########################
# Create figure for features
fig1 = mlab.figure('Models', bgcolor=(1, 1, 1), size=(1000, 800))
fig1.scene.parallel_projection = False
# Indices
global file_i
file_i = 0
def update_scene():
# clear figure
mlab.clf(fig1)
# Plot new data feature
points = all_points[file_i]
# Rescale points for visu
points = (points * 1.5 + np.array([1.0, 1.0, 1.0])) * 50.0
# Show point clouds colorized with activations
activations = mlab.points3d(points[:, 0],
points[:, 1],
points[:, 2],
points[:, 2],
scale_factor=3.0,
scale_mode='none',
figure=fig1)
# New title
mlab.title(str(file_i), color=(0, 0, 0), size=0.3, height=0.01)
text = '<--- (press g for previous)' + 50 * ' ' + '(press h for next) --->'
mlab.text(0.01, 0.01, text, color=(0, 0, 0), width=0.98)
mlab.orientation_axes()
return
def keyboard_callback(vtk_obj, event):
global file_i
if vtk_obj.GetKeyCode() in ['g', 'G']:
file_i = (file_i - 1) % len(all_points)
update_scene()
elif vtk_obj.GetKeyCode() in ['h', 'H']:
file_i = (file_i + 1) % len(all_points)
update_scene()
return
# Draw a first plot
update_scene()
fig1.scene.interactor.add_observer('KeyPressEvent', keyboard_callback)
mlab.show()
def show_ModelNet_examples(clouds, cloud_normals=None, cloud_labels=None):
from mayavi import mlab
###########################
# Interactive visualization
###########################
# Create figure for features
fig1 = mlab.figure('Models', bgcolor=(1, 1, 1), size=(1000, 800))
fig1.scene.parallel_projection = False
if cloud_labels is None:
cloud_labels = [points[:, 2] for points in clouds]
# Indices
global file_i, show_normals
file_i = 0
show_normals = True
def update_scene():
# clear figure
mlab.clf(fig1)
# Plot new data feature
points = clouds[file_i]
labels = cloud_labels[file_i]
if cloud_normals is not None:
normals = cloud_normals[file_i]
else:
normals = None
# Rescale points for visu
points = (points * 1.5 + np.array([1.0, 1.0, 1.0])) * 50.0
# Show point clouds colorized with activations
activations = mlab.points3d(points[:, 0],
points[:, 1],
points[:, 2],
labels,
scale_factor=3.0,
scale_mode='none',
figure=fig1)
if normals is not None and show_normals:
activations = mlab.quiver3d(points[:, 0],
points[:, 1],
points[:, 2],
normals[:, 0],
normals[:, 1],
normals[:, 2],
scale_factor=10.0,
scale_mode='none',
figure=fig1)
# New title
mlab.title(str(file_i), color=(0, 0, 0), size=0.3, height=0.01)
text = '<--- (press g for previous)' + 50 * ' ' + '(press h for next) --->'
mlab.text(0.01, 0.01, text, color=(0, 0, 0), width=0.98)
mlab.orientation_axes()
return
def keyboard_callback(vtk_obj, event):
global file_i, show_normals
if vtk_obj.GetKeyCode() in ['g', 'G']:
file_i = (file_i - 1) % len(clouds)
update_scene()
elif vtk_obj.GetKeyCode() in ['h', 'H']:
file_i = (file_i + 1) % len(clouds)
update_scene()
elif vtk_obj.GetKeyCode() in ['n', 'N']:
show_normals = not show_normals
update_scene()
return
# Draw a first plot
update_scene()
fig1.scene.interactor.add_observer('KeyPressEvent', keyboard_callback)
mlab.show()
def show_neighbors(query, supports, neighbors):
from mayavi import mlab
###########################
# Interactive visualization
###########################
# Create figure for features
fig1 = mlab.figure('Models', bgcolor=(1, 1, 1), size=(1000, 800))
fig1.scene.parallel_projection = False
# Indices
global file_i
file_i = 0
def update_scene():
# clear figure
mlab.clf(fig1)
# Rescale points for visu
p1 = (query * 1.5 + np.array([1.0, 1.0, 1.0])) * 50.0
p2 = (supports * 1.5 + np.array([1.0, 1.0, 1.0])) * 50.0
l1 = p1[:, 2]*0
l1[file_i] = 1
l2 = p2[:, 2]*0 + 2
l2[neighbors[file_i]] = 3
# Show point clouds colorized with activations
activations = mlab.points3d(p1[:, 0],
p1[:, 1],
p1[:, 2],
l1,
scale_factor=2.0,
scale_mode='none',
vmin=0.0,
vmax=3.0,
figure=fig1)
activations = mlab.points3d(p2[:, 0],
p2[:, 1],
p2[:, 2],
l2,
scale_factor=3.0,
scale_mode='none',
vmin=0.0,
vmax=3.0,
figure=fig1)
# New title
mlab.title(str(file_i), color=(0, 0, 0), size=0.3, height=0.01)
text = '<--- (press g for previous)' + 50 * ' ' + '(press h for next) --->'
mlab.text(0.01, 0.01, text, color=(0, 0, 0), width=0.98)
mlab.orientation_axes()
return
def keyboard_callback(vtk_obj, event):
global file_i
if vtk_obj.GetKeyCode() in ['g', 'G']:
file_i = (file_i - 1) % len(query)
update_scene()
elif vtk_obj.GetKeyCode() in ['h', 'H']:
file_i = (file_i + 1) % len(query)
update_scene()
return
# Draw a first plot
update_scene()
fig1.scene.interactor.add_observer('KeyPressEvent', keyboard_callback)
mlab.show()
def show_input_batch(batch):
from mayavi import mlab
###########################
# Interactive visualization
###########################
# Create figure for features
fig1 = mlab.figure('Input', bgcolor=(1, 1, 1), size=(1000, 800))
fig1.scene.parallel_projection = False
# Unstack batch
all_points = batch.unstack_points()
all_neighbors = batch.unstack_neighbors()
all_pools = batch.unstack_pools()
# Indices
global b_i, l_i, neighb_i, show_pools
b_i = 0
l_i = 0
neighb_i = 0
show_pools = False
def update_scene():
# clear figure
mlab.clf(fig1)
# Rescale points for visu
p = (all_points[l_i][b_i] * 1.5 + np.array([1.0, 1.0, 1.0])) * 50.0
labels = p[:, 2]*0
if show_pools:
p2 = (all_points[l_i+1][b_i][neighb_i:neighb_i+1] * 1.5 + np.array([1.0, 1.0, 1.0])) * 50.0
p = np.vstack((p, p2))
labels = np.hstack((labels, np.ones((1,), dtype=np.int32)*3))
pool_inds = all_pools[l_i][b_i][neighb_i]
pool_inds = pool_inds[pool_inds >= 0]
labels[pool_inds] = 2
else:
neighb_inds = all_neighbors[l_i][b_i][neighb_i]
neighb_inds = neighb_inds[neighb_inds >= 0]
labels[neighb_inds] = 2
labels[neighb_i] = 3
# Show point clouds colorized with activations
mlab.points3d(p[:, 0],
p[:, 1],
p[:, 2],
labels,
scale_factor=2.0,
scale_mode='none',
vmin=0.0,
vmax=3.0,
figure=fig1)
"""
mlab.points3d(p[-2:, 0],
p[-2:, 1],
p[-2:, 2],
labels[-2:]*0 + 3,
scale_factor=0.16 * 1.5 * 50,
scale_mode='none',
mode='cube',
vmin=0.0,
vmax=3.0,
figure=fig1)
mlab.points3d(p[-1:, 0],
p[-1:, 1],
p[-1:, 2],
labels[-1:]*0 + 2,
scale_factor=0.16 * 2 * 2.5 * 1.5 * 50,
scale_mode='none',
mode='sphere',
vmin=0.0,
vmax=3.0,
figure=fig1)
"""
# New title
title_str = '<([) b_i={:d} (])> <(,) l_i={:d} (.)> <(N) n_i={:d} (M)>'.format(b_i, l_i, neighb_i)
mlab.title(title_str, color=(0, 0, 0), size=0.3, height=0.90)
if show_pools:
text = 'pools (switch with G)'
else:
text = 'neighbors (switch with G)'
mlab.text(0.01, 0.01, text, color=(0, 0, 0), width=0.3)
mlab.orientation_axes()
return
def keyboard_callback(vtk_obj, event):
global b_i, l_i, neighb_i, show_pools
if vtk_obj.GetKeyCode() in ['[', '{']:
b_i = (b_i - 1) % len(all_points[l_i])
neighb_i = 0
update_scene()
elif vtk_obj.GetKeyCode() in [']', '}']:
b_i = (b_i + 1) % len(all_points[l_i])
neighb_i = 0
update_scene()
elif vtk_obj.GetKeyCode() in [',', '<']:
if show_pools:
l_i = (l_i - 1) % (len(all_points) - 1)
else:
l_i = (l_i - 1) % len(all_points)
neighb_i = 0
update_scene()
elif vtk_obj.GetKeyCode() in ['.', '>']:
if show_pools:
l_i = (l_i + 1) % (len(all_points) - 1)
else:
l_i = (l_i + 1) % len(all_points)
neighb_i = 0
update_scene()
elif vtk_obj.GetKeyCode() in ['n', 'N']:
neighb_i = (neighb_i - 1) % all_points[l_i][b_i].shape[0]
update_scene()
elif vtk_obj.GetKeyCode() in ['m', 'M']:
neighb_i = (neighb_i + 1) % all_points[l_i][b_i].shape[0]
update_scene()
elif vtk_obj.GetKeyCode() in ['g', 'G']:
if l_i < len(all_points) - 1:
show_pools = not show_pools
neighb_i = 0
update_scene()
return
# Draw a first plot
update_scene()
fig1.scene.interactor.add_observer('KeyPressEvent', keyboard_callback)
mlab.show()