forked from animate1978/MB-Lab
-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathanimationengine.py
1566 lines (1324 loc) · 66.1 KB
/
animationengine.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
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
913
914
915
916
917
918
919
920
921
922
923
924
925
926
927
928
929
930
931
932
933
934
935
936
937
938
939
940
941
942
943
944
945
946
947
948
949
950
951
952
953
954
955
956
957
958
959
960
961
962
963
964
965
966
967
968
969
970
971
972
973
974
975
976
977
978
979
980
981
982
983
984
985
986
987
988
989
990
991
992
993
994
995
996
997
998
999
1000
# MB-Lab
#
# MB-Lab fork website : https://github.com/animate1978/MB-Lab
#
# ##### BEGIN GPL LICENSE BLOCK #####
#
# This program is free software; you can redistribute it and/or
# modify it under the terms of the GNU General Public License
# as published by the Free Software Foundation; either version 3
# of the License, or (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program; if not, write to the Free Software Foundation,
# Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
#
# ##### END GPL LICENSE BLOCK #####
#
# ManuelbastioniLAB - Copyright (C) 2015-2018 Manuel Bastioni
import logging
import os
import json
import time
from functools import lru_cache
import mathutils
import bpy
from . import algorithms, utils, file_ops, object_ops
from .utils import get_active_armature
logger = logging.getLogger(__name__)
# ------------------------------------------------------------------------
# Animation Engine
# ------------------------------------------------------------------------
class RetargetEngine:
def __init__(self):
self.has_data = False
self.femaleposes_exist = False
self.maleposes_exist = False
self.data_path = file_ops.get_data_path()
self.maleposes_path = os.path.join(self.data_path, self.data_path, "poses", "male_poses")
self.femaleposes_path = os.path.join(self.data_path, self.data_path, "poses", "female_poses")
if os.path.isdir(self.maleposes_path):
self.maleposes_exist = True
if os.path.isdir(self.femaleposes_path):
self.femaleposes_exist = True
self.body_name = ""
self.armature_name = ""
self.skeleton_mapped = {}
self.lib_filepath = file_ops.get_blendlibrary_path()
self.knowledge_path = os.path.join(self.data_path, "retarget_knowledge.json")
if os.path.isfile(self.lib_filepath) and os.path.isfile(self.knowledge_path):
self.knowledge_database = file_ops.load_json_data(self.knowledge_path, "Skeleton knowledge data")
self.local_rotation_bones = self.knowledge_database["local_rotation_bones"]
self.last_selected_bone_name = None
self.stored_animations = {}
self.correction_is_sync = True
self.is_animated_bone = ""
self.rot_type = ""
self.has_data = True
else:
logger.critical("Retarget database not found. Please check your Blender addons directory.")
@staticmethod
def get_selected_posebone():
if bpy.context.selected_pose_bones:
if bpy.context.selected_pose_bones:
return bpy.context.selected_pose_bones[0]
return None
def is_editable_bone(self):
armat = get_active_armature()
if armat:
if armat.animation_data:
if armat.animation_data.action:
if self.rot_type in ["EULER", "QUATERNION"]:
self.is_animated_bone = "VALID_BONE"
else:
self.is_animated_bone = "The bone has not anim. data"
else:
self.is_animated_bone = "{0} has not action data".format(armat.name)
else:
self.is_animated_bone = "{0} has not animation data".format(armat.name)
else:
self.is_animated_bone = "No armature selected"
@staticmethod
def get_action(target_armature):
if target_armature and target_armature.animation_data:
return target_armature.animation_data.action
return None
def check_correction_sync(self):
scn = bpy.context.scene
selected_bone = self.get_selected_posebone()
if selected_bone:
if self.last_selected_bone_name != selected_bone.name:
self.get_bone_rot_type()
offsets = self.get_offset_values()
if scn.mblab_rot_offset_0 != offsets[0]:
self.correction_is_sync = False
if scn.mblab_rot_offset_1 != offsets[1]:
self.correction_is_sync = False
if scn.mblab_rot_offset_2 != offsets[2]:
self.correction_is_sync = False
self.is_editable_bone()
self.last_selected_bone_name = selected_bone.name
def get_offset_values(self):
offsets = [0, 0, 0]
for i in (0, 1, 2):
if self.rot_type == "QUATERNION":
channel = i+1
else:
channel = i
armat_name, animation_curve, animation_data_id = self.get_curve_data(channel)
if armat_name in self.stored_animations.keys():
if animation_data_id in self.stored_animations[armat_name].keys():
animation_data = self.stored_animations[armat_name][animation_data_id]
if animation_curve:
if animation_curve.keyframe_points:
offsets[i] = animation_curve.keyframe_points[0].co[1] - animation_data[0]
return offsets
def identify_curve_rot(self, bone):
r_type = "NO_CURVES"
armat = get_active_armature()
if armat:
action = self.get_action(armat)
if action and bone:
d_path1 = f'pose.bones["{bone.name}"].rotation_quaternion'
d_path2 = f'pose.bones["{bone.name}"].rotation_axis_angle'
d_path3 = f'pose.bones["{bone.name}"].rotation_euler'
animation_curve1 = action.fcurves.find(d_path1, index=0)
animation_curve2 = action.fcurves.find(d_path2, index=0)
animation_curve3 = action.fcurves.find(d_path3, index=0)
if animation_curve1:
r_type = "QUATERNION"
if animation_curve2:
r_type = "AXIS_ANGLE"
if animation_curve3:
r_type = "EULER"
return r_type
def get_bone_rot_type(self):
selected_bone = self.get_selected_posebone()
self.rot_type = self.identify_curve_rot(selected_bone)
def get_bone_curve_id(self, selected_bone):
if self.rot_type == "QUATERNION":
return f'pose.bones["{selected_bone.name}"].rotation_quaternion'
if self.rot_type == "EULER":
return f'pose.bones["{selected_bone.name}"].rotation_euler'
return None
def get_curve_data(self, channel):
armat = get_active_armature()
d_path = None
if armat:
action = self.get_action(armat)
if action:
selected_bone = self.get_selected_posebone()
if selected_bone:
d_path = self.get_bone_curve_id(selected_bone)
if d_path:
animation_curve = action.fcurves.find(d_path, index=channel)
animation_data_id = f'{d_path}{str(channel)}'
if animation_curve:
return (armat.name, animation_curve, animation_data_id)
return (None, None, None)
def reset_bones_correction(self):
self.stored_animations = {}
def correct_bone_angle(self, channel, value):
scn = bpy.context.scene
if self.rot_type == "QUATERNION":
channel += 1
armat_name, animation_curve, animation_data_id = self.get_curve_data(channel)
if armat_name and animation_curve and animation_data_id:
if armat_name not in self.stored_animations.keys():
self.stored_animations[armat_name] = {}
if animation_data_id not in self.stored_animations[armat_name].keys():
animation_data = []
for kpoint in animation_curve.keyframe_points:
animation_data.append(kpoint.co[1])
self.stored_animations[armat_name][animation_data_id] = animation_data
else:
animation_data = self.stored_animations[armat_name][animation_data_id]
for i, _ in enumerate(animation_data):
animation_curve.keyframe_points[i].co[1] = animation_data[i] + value
animation_curve.update()
scn.frame_set(scn.frame_current)
def align_bones_z_axis(self, target_armature, source_armature):
armature_z_axis = {}
if target_armature:
if source_armature:
logger.info("Aligning Z axis of %s with Z axis of %s",
target_armature.name, source_armature.name)
algorithms.select_and_change_mode(source_armature, 'EDIT')
for x_bone in target_armature.data.bones:
b_name = x_bone.name
source_bone_name = self.get_mapped_name(b_name)
if source_bone_name is not None:
armature_z_axis[b_name] = source_armature.data.edit_bones[source_bone_name].z_axis.copy()
else:
logger.debug("Bone %s non mapped", b_name)
algorithms.select_and_change_mode(source_armature, 'POSE')
algorithms.select_and_change_mode(target_armature, 'EDIT')
for armat_bone in target_armature.data.edit_bones:
if armat_bone.name in armature_z_axis:
z_axis = armature_z_axis[armat_bone.name]
armat_bone.align_roll(z_axis)
algorithms.select_and_change_mode(target_armature, 'POSE')
def reset_skeleton_mapped(self):
self.skeleton_mapped = {}
def init_skeleton_map(self, source_armat):
self.reset_skeleton_mapped()
self.already_mapped_bones = []
self.spine_bones_names = None
self.rarm_bones_names = None
self.larm_bones_names = None
self.rleg_bones_names = None
self.lleg_bones_names = None
self.head_bones_names = None
self.pelvis_bones_names = None
self.rtoe1_bones_names = None
self.rtoe2_bones_names = None
self.rtoe3_bones_names = None
self.rtoe4_bones_names = None
self.rtoe5_bones_names = None
self.ltoe1_bones_names = None
self.ltoe2_bones_names = None
self.ltoe3_bones_names = None
self.ltoe4_bones_names = None
self.ltoe5_bones_names = None
self.rfinger0_bones_names = None
self.rfinger1_bones_names = None
self.rfinger2_bones_names = None
self.rfinger3_bones_names = None
self.rfinger4_bones_names = None
self.lfinger0_bones_names = None
self.lfinger1_bones_names = None
self.lfinger2_bones_names = None
self.lfinger3_bones_names = None
self.lfinger4_bones_names = None
self.map_main_bones(source_armat)
@staticmethod
def name_combinations(bone_identifiers, side):
combinations = []
if side == 'RIGHT':
side_id = ("r", "right")
junctions = (".", "_", "-", "")
elif side == 'LEFT':
side_id = ("l", "left")
junctions = (".", "_", "-", "")
else:
side_id = [""]
junctions = [""]
for b_id in bone_identifiers:
for s_id in side_id:
for junct in junctions:
combinations.append(f'{b_id}{junct}{s_id}')
combinations.append(f'{s_id}{junct}{b_id}')
return combinations
def get_bone_by_exact_id(self, bones_to_scan, bone_identifiers, side):
if bones_to_scan:
name_combinations = self.name_combinations(bone_identifiers, side)
for b_name in bones_to_scan:
if b_name.lower() in name_combinations:
return b_name
return None
def get_bone_by_childr(self, armat, bones_to_scan, childr_identifiers):
if childr_identifiers:
for bone_name in bones_to_scan:
x_bone = self.get_bone(armat, bone_name)
if not x_bone:
return None
for ch_bone in x_bone.children:
for ch_id in childr_identifiers:
c1 = algorithms.is_string_in_string(ch_id, ch_bone.name)
c2 = ch_bone.name in bones_to_scan
c3 = algorithms.is_too_much_similar(x_bone.name, ch_bone.name)
if c1 and c2 and not c3:
return x_bone.name
return None
@staticmethod
def get_bones_by_index(bones_chain, index_data):
index = None
if bones_chain:
if len(index_data) == 1:
if index_data[0] == "LAST":
index = len(bones_chain)-1
else:
index = index_data[0]
if len(index_data) == 3:
if len(bones_chain) == index_data[0]:
index = index_data[1]
else:
index = index_data[2]
if index == "None":
index = None
if index is not None:
try:
return bones_chain[index]
except IndexError:
logger.warning("The chain %s of mocap file has less bones than the chain in MB-Lab", bones_chain)
return None
# def get_bones_by_parent(self, armat, bones_to_scan, parent_IDs):
# found_bones = set()
# for bone_name in bones_to_scan:
# parent_name = self.bone_parent_name(armat, bone_name)
# for pr_id in parent_IDs:
# if algorithms.is_string_in_string(pr_id, parent_name):
# found_bones.add(bone_name)
# return found_bones
@staticmethod
def get_bone_chains(armat, bone_names):
found_chains = []
for bone_name in bone_names:
bn = armat.data.bones[bone_name]
chain = [bone_name] + [b.name for b in bn.parent_recursive]
found_chains.append(chain)
return found_chains
@staticmethod
def get_all_bone_names(armat):
bone_names = []
for bn in armat.data.bones:
bone_names.append(bn.name)
return bone_names
@staticmethod
@lru_cache(maxsize=2)
def generate_bones_ids(side):
bone_ids = ("forearm", "elbow", "lowerarm", "hand", "wrist", "finger", "thumb", "index",
"ring", "pink", "thigh", "upperleg", "upper_leg", "leg", "knee", "shin", "calf",
"lowerleg", "lower_leg", "toe", "ball", "foot")
bn_pos = "r" if side == "RIGHT" else "l"
combo_bones_start = []
combo_bones_end = []
for b_id in bone_ids:
combo_bones_start.append(f'{bn_pos}{b_id}')
combo_bones_end.append(f'{b_id}{bn_pos}')
return combo_bones_start, combo_bones_end
def is_in_side(self, bone_names, side):
score_level = 0.0
if side == "RIGHT":
id_side2 = "right"
id_side3 = ("r.", "r_")
id_side4 = ("_r", ".r")
if side == "LEFT":
id_side2 = "left"
id_side3 = ("l.", "l_")
id_side4 = ("_l", ".l")
combo_bones_start, combo_bones_end = self.generate_bones_ids(side)
for bone_name in bone_names:
bone_name = bone_name.lower()
if len(bone_name) > 3:
c1 = bone_name[:2] in id_side3
c2 = bone_name[-2:] in id_side4
c3 = id_side2 in bone_name
c4 = algorithms.is_in_list(bone_names, combo_bones_start, "START")
c5 = algorithms.is_in_list(bone_names, combo_bones_end, "END")
if c1 or c2 or c3 or c4 or c5:
score_level += 1
if bone_names:
return score_level/len(bone_names)
return 0
@staticmethod
def order_with_list(bones_set, bones_list):
ordered_bones = []
for bone in bones_list:
if bone in bones_set:
ordered_bones.append(bone)
return ordered_bones
def chains_intersection(self, chains):
chain_sets = []
chain_inters = None
result_chain = []
for chain in chains:
chain_sets.append(set(chain))
for i, chain in enumerate(chain_sets):
chain_inters = chain if chain_inters is None else chain_inters.intersection(chain)
result_chain = self.order_with_list(chain_inters, chains[i])
return result_chain
@staticmethod
def filter_chains_by_max_length(chains):
longer_chains = []
max_length = 0
for chain in chains:
max_length = max(max_length, len(chain))
for chain in chains:
if len(chain) == max_length:
longer_chains.append(chain)
return longer_chains
def chains_difference(self, chain_list, subchain_list):
subchain_set = set(subchain_list)
chain_set = set(chain_list)
d_chain = chain_set.difference(subchain_set)
return self.order_with_list(d_chain, chain_list)
def filter_chains_by_side(self, chains):
left_chains = []
right_chains = []
center_chains = []
for chain in chains:
score_left = self.is_in_side(chain, "LEFT")
score_right = self.is_in_side(chain, "RIGHT")
if score_left > 0:
left_chains.append(chain)
elif score_right > 0:
right_chains.append(chain)
else:
center_chains.append(chain)
if not center_chains:
score_threshold = 0
for chain in chains:
score_left = self.is_in_side(chain, "LEFT")
score_right = self.is_in_side(chain, "RIGHT")
score_center = 1.0-score_left-score_right
if score_center > score_threshold:
score_threshold = score_center
center_chain = chain
center_chains.append(center_chain)
return left_chains, center_chains, right_chains
@staticmethod
def filter_chains_by_tail(chains, chain_ids):
target_chains_lists = []
if chains:
for chain in chains:
chain_tail = chain[0]
if algorithms.is_in_list(chain_ids, [chain_tail]):
target_chains_lists.append(chain)
return target_chains_lists
@staticmethod
def clear_chain_by_dot_product(chain, armature):
algorithms.select_and_change_mode(armature, 'EDIT')
if len(chain) > 2:
edit_bones = algorithms.get_edit_bones(armature)
bone_name = chain[0]
if bone_name in edit_bones:
e_bone = edit_bones[bone_name]
if e_bone.parent:
v1 = e_bone.vector.normalized()
v2 = e_bone.parent.vector.normalized()
if v1.dot(v2) < 0.5:
logger.info("Retarget: Bone %s removed BY DOT", bone_name)
chain.remove(bone_name)
algorithms.select_and_change_mode(armature, 'POSE') # TODO: store the status and restore it
return chain
@staticmethod
def clear_chain_by_length(chain, armature):
algorithms.select_and_change_mode(armature, 'EDIT')
for bone_name in chain:
edit_bones = algorithms.get_edit_bones(armature)
if bone_name in edit_bones:
e_bone = edit_bones[bone_name]
if e_bone.parent:
if e_bone.length < e_bone.parent.length/8:
logger.info("Retarget: Bone %s removed BY LENGTH", bone_name)
chain.remove(bone_name)
algorithms.select_and_change_mode(armature, 'POSE') # TODO: store the status and restore it
return chain
def filter_chains_by_dotprod(self, armature):
self.spine_bones_names = self.clear_chain_by_dot_product(self.spine_bones_names, armature)
self.head_bones_names = self.clear_chain_by_dot_product(self.head_bones_names, armature)
self.rarm_bones_names = self.clear_chain_by_dot_product(self.rarm_bones_names, armature)
self.larm_bones_names = self.clear_chain_by_dot_product(self.larm_bones_names, armature)
self.pelvis_bones_names = self.clear_chain_by_dot_product(self.pelvis_bones_names, armature)
self.ltoe_and_leg_names = self.clear_chain_by_dot_product(self.ltoe_and_leg_names, armature)
self.rtoe_and_leg_names = self.clear_chain_by_dot_product(self.rtoe_and_leg_names, armature)
self.rfinger0_bones_names = self.clear_chain_by_dot_product(self.rfinger0_bones_names, armature)
self.rfinger1_bones_names = self.clear_chain_by_dot_product(self.rfinger1_bones_names, armature)
self.rfinger2_bones_names = self.clear_chain_by_dot_product(self.rfinger2_bones_names, armature)
self.rfinger3_bones_names = self.clear_chain_by_dot_product(self.rfinger3_bones_names, armature)
self.rfinger4_bones_names = self.clear_chain_by_dot_product(self.rfinger4_bones_names, armature)
self.lfinger0_bones_names = self.clear_chain_by_dot_product(self.lfinger0_bones_names, armature)
self.lfinger1_bones_names = self.clear_chain_by_dot_product(self.lfinger1_bones_names, armature)
self.lfinger2_bones_names = self.clear_chain_by_dot_product(self.lfinger2_bones_names, armature)
self.lfinger3_bones_names = self.clear_chain_by_dot_product(self.lfinger3_bones_names, armature)
self.lfinger4_bones_names = self.clear_chain_by_dot_product(self.lfinger4_bones_names, armature)
def filter_chains_by_length(self, armature):
self.head_bones_names = self.clear_chain_by_length(self.head_bones_names, armature)
self.rarm_bones_names = self.clear_chain_by_length(self.rarm_bones_names, armature)
self.larm_bones_names = self.clear_chain_by_length(self.larm_bones_names, armature)
self.rleg_bones_names = self.clear_chain_by_length(self.rleg_bones_names, armature)
self.lleg_bones_names = self.clear_chain_by_length(self.lleg_bones_names, armature)
self.ltoe_and_leg_names = self.clear_chain_by_length(self.ltoe_and_leg_names, armature)
self.rtoe_and_leg_names = self.clear_chain_by_length(self.rtoe_and_leg_names, armature)
self.rfinger0_bones_names = self.clear_chain_by_length(self.rfinger0_bones_names, armature)
self.rfinger1_bones_names = self.clear_chain_by_length(self.rfinger1_bones_names, armature)
self.rfinger2_bones_names = self.clear_chain_by_length(self.rfinger2_bones_names, armature)
self.rfinger3_bones_names = self.clear_chain_by_length(self.rfinger3_bones_names, armature)
self.rfinger4_bones_names = self.clear_chain_by_length(self.rfinger4_bones_names, armature)
self.lfinger0_bones_names = self.clear_chain_by_length(self.lfinger0_bones_names, armature)
self.lfinger1_bones_names = self.clear_chain_by_length(self.lfinger1_bones_names, armature)
self.lfinger2_bones_names = self.clear_chain_by_length(self.lfinger2_bones_names, armature)
self.lfinger3_bones_names = self.clear_chain_by_length(self.lfinger3_bones_names, armature)
self.lfinger4_bones_names = self.clear_chain_by_length(self.lfinger4_bones_names, armature)
@staticmethod
def filter_chains_by_id(chains, chain_ids):
target_chains_lists = []
for chain in chains:
if algorithms.is_in_list(chain_ids, chain):
target_chains_lists.append(chain)
return target_chains_lists
@staticmethod
def filter_chains_by_order(chains, n_ord):
named_fingers = ("thu", "ind", "mid", "ring", "pink")
identifiers = []
for chain in chains:
if chain:
identifiers.append(chain[0])
identifiers.sort()
result_chain = []
chain_order = None
chain_id = None
if algorithms.is_in_list(named_fingers, identifiers):
chain_order = "NAMED"
else:
chain_order = "NUMBERED"
if chain_order == "NAMED":
chain_id = named_fingers[n_ord]
if chain_order == "NUMBERED":
if len(identifiers) > n_ord:
chain_id = identifiers[n_ord]
if chain_id:
chain_id = chain_id.lower()
for chain in chains:
chain_tail = chain[0]
chain_tail = chain_tail.lower()
if chain_id in chain_tail:
result_chain = chain
return result_chain
return result_chain
def identify_bone_chains(self, chains):
left_chains, center_chains, right_chains = self.filter_chains_by_side(chains)
# ARM_CHAIN_IDS
arm_chain_ids = ("arm", "elbow", "hand", "wrist", "finger", "thumb", "index",
"ring", "pink", "mid")
arms_tail_chains = self.filter_chains_by_id(chains, arm_chain_ids)
arms_tail_chains = self.filter_chains_by_max_length(arms_tail_chains)
spine_chain = self.chains_intersection(arms_tail_chains)
right_arm_tail_chains = self.filter_chains_by_tail(right_chains, arm_chain_ids)
right_arm_tail_chains = self.filter_chains_by_max_length(right_arm_tail_chains)
r_arm_spine_chain = self.chains_intersection(right_arm_tail_chains)
right_arm_chain = self.chains_difference(r_arm_spine_chain, spine_chain)
left_arm_tail_chains = self.filter_chains_by_tail(left_chains, arm_chain_ids)
left_arm_tail_chains = self.filter_chains_by_max_length(left_arm_tail_chains)
l_arm_spine_chain = self.chains_intersection(left_arm_tail_chains)
left_arm_chain = self.chains_difference(l_arm_spine_chain, spine_chain)
# HEAD_CHAIN_IDS
head_chain_ids = ("head", "neck", "skull", "face", "spine")
head_tail_chains = self.filter_chains_by_id(center_chains, head_chain_ids)
head_tail_chains = self.filter_chains_by_max_length(head_tail_chains)
head_and_spine_chains = self.chains_intersection(head_tail_chains)
head_chain = self.chains_difference(head_and_spine_chains, spine_chain)
# FINGER_CHAIN_IDS
finger_chain_ids = ("finger", "thumb", "index", "ring", "pink", "mid")
# RIGHT
right_fingers_tail_chains = self.filter_chains_by_tail(right_chains, finger_chain_ids)
r_finger_arm_spine_chain = self.chains_intersection(right_fingers_tail_chains)
right_fingers_chain = [self.chains_difference(fingr, r_finger_arm_spine_chain)
for fingr in right_fingers_tail_chains]
# LEFT
left_fingers_tail_chains = self.filter_chains_by_tail(left_chains, finger_chain_ids)
l_finger_arm_spine_chain = self.chains_intersection(left_fingers_tail_chains)
left_fingers_chain = [self.chains_difference(fingr, l_finger_arm_spine_chain)
for fingr in left_fingers_tail_chains]
# FOOT_CHAIN_IDS
foot_chain_ids = ("foot", "ankle", "toe", "ball")
right_foot_tail_chains = self.filter_chains_by_tail(right_chains, foot_chain_ids)
right_foot_tail_chains.sort()
self.rtoe_and_leg_names = right_foot_tail_chains[0]
right_foot_tail_chains = self.filter_chains_by_max_length(right_foot_tail_chains)
r_leg_and_spine_chain = self.chains_intersection(right_foot_tail_chains)
right_leg_chain = self.chains_difference(r_leg_and_spine_chain, spine_chain)
right_toes_chain = [self.chains_difference(toe, r_leg_and_spine_chain) for toe in right_foot_tail_chains]
right_toes_chain = self.filter_chains_by_max_length(right_toes_chain)
left_foot_tail_chains = self.filter_chains_by_tail(left_chains, foot_chain_ids)
left_foot_tail_chains.sort()
self.ltoe_and_leg_names = left_foot_tail_chains[0]
left_foot_tail_chains = self.filter_chains_by_max_length(left_foot_tail_chains)
l_leg_and_spine_chain = self.chains_intersection(left_foot_tail_chains)
left_leg_chain = self.chains_difference(l_leg_and_spine_chain, spine_chain)
left_toes_chain = [self.chains_difference(toe, l_leg_and_spine_chain) for toe in left_foot_tail_chains]
left_toes_chain = self.filter_chains_by_max_length(left_toes_chain)
feet_tail_chains = self.filter_chains_by_tail(chains, foot_chain_ids)
# TODO not used
# leg_chain_IDs = ["thigh", "upperleg", "upper_leg", "leg", "knee", "shin",
# "calf", "lowerleg", "lower_leg", "foot", "ankle", "toe", "ball"]
pelvis_chain = self.chains_intersection(feet_tail_chains)
self.spine_bones_names = spine_chain
self.head_bones_names = head_chain
self.rarm_bones_names = right_arm_chain
self.larm_bones_names = left_arm_chain
self.rleg_bones_names = right_leg_chain
self.lleg_bones_names = left_leg_chain
self.pelvis_bones_names = pelvis_chain
self.rfinger0_bones_names = self.filter_chains_by_order(right_fingers_chain, 0)
self.rfinger1_bones_names = self.filter_chains_by_order(right_fingers_chain, 1)
self.rfinger2_bones_names = self.filter_chains_by_order(right_fingers_chain, 2)
self.rfinger3_bones_names = self.filter_chains_by_order(right_fingers_chain, 3)
self.rfinger4_bones_names = self.filter_chains_by_order(right_fingers_chain, 4)
self.lfinger0_bones_names = self.filter_chains_by_order(left_fingers_chain, 0)
self.lfinger1_bones_names = self.filter_chains_by_order(left_fingers_chain, 1)
self.lfinger2_bones_names = self.filter_chains_by_order(left_fingers_chain, 2)
self.lfinger3_bones_names = self.filter_chains_by_order(left_fingers_chain, 3)
self.lfinger4_bones_names = self.filter_chains_by_order(left_fingers_chain, 4)
@staticmethod
def get_ending_bones(armat):
found_bones = set()
for bn in armat.data.bones:
if not bn.children:
found_bones.add(bn.name)
return found_bones
@staticmethod
def string_similarity(main_string, identifiers, side):
m_string = main_string.lower()
sub_string_found = False
substrings = []
if side == 'LEFT':
substrings = ["l-", "-l", "_l", "l_", ".l", "l.", "left"]
if side == 'RIGHT':
substrings = ["r-", "-r", "_r", "r_", ".r", "r.", "right"]
for id_string in identifiers:
if id_string in m_string:
sub_string_found = True
if sub_string_found:
strings_to_subtract = identifiers + substrings
for s_string in strings_to_subtract:
s_string = s_string.lower()
if s_string in m_string:
m_string = m_string.replace(s_string, "")
return len(m_string)
return 1000
def get_bone_by_similar_id(self, bones_to_scan, bone_identifiers, side):
diff_length = 100
result = None
if bones_to_scan:
for bone_name in bones_to_scan:
score = self.string_similarity(bone_name, bone_identifiers, side)
if score < diff_length:
diff_length = score
result = bone_name
return result
def find_bone(self, armat, bone_type, search_method):
if not self.knowledge_database:
return None
bone_knowledge = self.knowledge_database[bone_type]
main_ids = bone_knowledge["main_IDs"]
children_ids = bone_knowledge["children_IDs"]
# parent_IDs = bone_knowledge["parent_IDs"]
side = bone_knowledge["side"]
chain_id = bone_knowledge["chain_ID"]
position_in_chain = bone_knowledge["position_in_chain"]
bones_chain = None
if chain_id == "spine_bones_names":
bones_chain = self.spine_bones_names
elif chain_id == "rarm_bones_names":
bones_chain = self.rarm_bones_names
elif chain_id == "larm_bones_names":
bones_chain = self.larm_bones_names
elif chain_id == "rleg_bones_names":
bones_chain = self.rleg_bones_names
elif chain_id == "lleg_bones_names":
bones_chain = self.lleg_bones_names
elif chain_id == "head_bones_names":
bones_chain = self.head_bones_names
elif chain_id == "pelvis_bones_names":
bones_chain = self.pelvis_bones_names
elif chain_id == "rtoe_and_leg_names":
bones_chain = self.rtoe_and_leg_names
elif chain_id == "ltoe_and_leg_names":
bones_chain = self.ltoe_and_leg_names
elif chain_id == "rfinger0_bones_names":
bones_chain = self.rfinger0_bones_names
elif chain_id == "rfinger1_bones_names":
bones_chain = self.rfinger1_bones_names
elif chain_id == "rfinger2_bones_names":
bones_chain = self.rfinger2_bones_names
elif chain_id == "rfinger3_bones_names":
bones_chain = self.rfinger3_bones_names
elif chain_id == "rfinger4_bones_names":
bones_chain = self.rfinger4_bones_names
elif chain_id == "lfinger0_bones_names":
bones_chain = self.lfinger0_bones_names
elif chain_id == "lfinger1_bones_names":
bones_chain = self.lfinger1_bones_names
elif chain_id == "lfinger2_bones_names":
bones_chain = self.lfinger2_bones_names
elif chain_id == "lfinger3_bones_names":
bones_chain = self.lfinger3_bones_names
elif chain_id == "lfinger4_bones_names":
bones_chain = self.lfinger4_bones_names
elif chain_id == "all_chains":
bones_chain = self.get_all_bone_names(armat)
if bones_chain:
all_methods = ["by_exact_name", "by_chain_index", "by_similar_name", "by_children"]
search_sequence = [search_method] # The first method is the one in knowledge
for methd in all_methods:
if methd not in search_sequence:
search_sequence.append(methd)
for s_method in search_sequence:
if s_method == "by_exact_name":
result = self.get_bone_by_exact_id(bones_chain, main_ids, side)
if result:
logger.info("Retarget: Bone %s found BY EXACT NAME", bone_type)
if result not in self.already_mapped_bones:
self.already_mapped_bones.append(result)
logger.info("Retarget: %s added to mapped bones", result)
return result
if s_method == "by_similar_name":
result = self.get_bone_by_similar_id(bones_chain, main_ids, side)
if result:
logger.info("Retarget: Bone %s found BY SIMILAR NAME", bone_type)
if result not in self.already_mapped_bones:
self.already_mapped_bones.append(result)
logger.info("Retarget: %s added to mapped bones", result)
return result
if s_method == "by_children":
result = self.get_bone_by_childr(armat, bones_chain, children_ids)
if result:
logger.info("Retarget: Bone %s found BY CHILDREN", bone_type)
if result not in self.already_mapped_bones:
self.already_mapped_bones.append(result)
logger.info("Retarget: %s added to mapped bones", result)
return result
if s_method == "by_chain_index":
result = self.get_bones_by_index(bones_chain, position_in_chain)
if result:
logger.info("Retarget: Bone %s found BY CHAIN INDEX", bone_type)
if result not in self.already_mapped_bones:
self.already_mapped_bones.append(result)
logger.info("Retarget: %s added to mapped bones", result)
return result
logger.warning("All retarget methods failed for %s.", bone_type)
#logger.warning(No candidates found in: {0}, or the candidate found is already mapped to another bone".format(bones_chain))
return None
def bone_parent_name(self, armat, b_name):
x_bone = self.get_bone(armat, b_name)
if x_bone:
if x_bone.parent:
return x_bone.parent.name
return None
def get_bone(self, armat, b_name, b_type="TARGET"):
if armat:
if b_type == "TARGET":
if b_name:
if b_name in armat.pose.bones:
return armat.pose.bones[b_name]
if b_type == "SOURCE":
b_name = self.get_mapped_name(b_name)
if b_name:
if b_name in armat.pose.bones:
return armat.pose.bones[b_name]
return None
@staticmethod
def get_target_editbone(armat, b_name,):
if bpy.context.object.mode == "EDIT":
if b_name:
ebone = algorithms.get_edit_bone(armat, b_name)
if ebone:
return ebone
logger.warning("%s not found in edit mode of target armature %s", b_name, armat)
return None
else:
logger.warning("Warning: Can't get the edit bone of %s because the mode is %s",
bpy.context.scene.objects.active, bpy.context.object.mode)
return None
def get_source_editbone(self, armat, b_name):
if bpy.context.object.mode == "EDIT":
b_name = self.get_mapped_name(b_name)
if b_name:
ebone = algorithms.get_edit_bone(armat, b_name)
if ebone:
return ebone
logger.warning("%s not found in edit mode of source armature %s", b_name, armat)
return None
else:
logger.warning("Warning: Can't get the edit bone of %s because the mode is %s",
bpy.context.scene.objects.active, bpy.context.object.mode)
return None
def get_mapped_name(self, b_name):
return self.skeleton_mapped.get(b_name)
def map_bone(self, armat, b_name, b_type, s_method):
mapped_name = self.find_bone(armat, b_type, s_method)
if mapped_name is not None:
self.skeleton_mapped[b_name] = mapped_name
def map_by_direct_parent(self, armat, childr_name, map_name):
childr_bone_name = self.get_mapped_name(childr_name)
if childr_bone_name:
parent_bone_name = self.bone_parent_name(armat, childr_bone_name)
if parent_bone_name:
if parent_bone_name not in self.already_mapped_bones:
self.skeleton_mapped[map_name] = parent_bone_name
self.already_mapped_bones.append(parent_bone_name)
return True
logger.warning("Error in mapping %s as direct parent of %s", map_name, childr_name)
return False
def map_main_bones(self, armat):
ending_bones = self.get_ending_bones(armat)
chains = self.get_bone_chains(armat, ending_bones)
self.identify_bone_chains(chains)
self.filter_chains_by_length(armat)
self.filter_chains_by_dotprod(armat)
for bone in (
("clavicle_L", "LCLAVICLE", "by_exact_name"),
("clavicle_R", "RCLAVICLE", "by_exact_name"),
("head", "HEAD", "by_exact_name"),
("lowerarm_R", "RFOREARM", "by_exact_name"),
("lowerarm_L", "LFOREARM", "by_exact_name"),
("upperarm_R", "RUPPERARM", "by_children"),
("upperarm_L", "LUPPERARM", "by_children"),
("hand_R", "RHAND", "by_exact_name"),
("hand_L", "LHAND", "by_exact_name"),
("breast_R", "RBREAST", "by_exact_name"),
("breast_L", "LBREAST", "by_exact_name"),
("calf_R", "RCALF", "by_exact_name"),
("calf_L", "LCALF", "by_exact_name"),
("foot_R", "RFOOT", "by_exact_name"),
("foot_L", "LFOOT", "by_exact_name"),
("toes_R", "RTOE", "by_exact_name"),
("toes_L", "LTOE", "by_exact_name"),
("pelvis", "PELVIS", "by_exact_name"),
("spine03", "CHEST", "by_chain_index"),
):
self.map_bone(armat, *bone)
if not self.map_by_direct_parent(armat, "head", "neck"):
self.map_bone(armat, "neck", "NECK", "by_similar_name") # TODO: integrate in find function
self.map_by_direct_parent(armat, "spine03", "spine02")
self.map_by_direct_parent(armat, "spine02", "spine01")
self.map_by_direct_parent(armat, "calf_R", "thigh_R")
self.map_by_direct_parent(armat, "calf_L", "thigh_L")
for bone in (
("thumb03_R", "RTHUMB03", "by_chain_index"),
("thumb02_R", "RTHUMB02", "by_chain_index"),
("thumb01_R", "RTHUMB01", "by_chain_index"),
("index03_R", "RINDEX03", "by_chain_index"),
("index02_R", "RINDEX02", "by_chain_index"),
("index01_R", "RINDEX01", "by_chain_index"),
("index00_R", "RINDEX00", "by_exact_name"),
("middle03_R", "RMIDDLE03", "by_chain_index"),
("middle02_R", "RMIDDLE02", "by_chain_index"),
("middle01_R", "RMIDDLE01", "by_chain_index"),
("middle00_R", "RMIDDLE00", "by_exact_name"),
("ring03_R", "RRING03", "by_chain_index"),
("ring02_R", "RRING02", "by_chain_index"),
("ring01_R", "RRING01", "by_chain_index"),
("ring00_R", "RRING00", "by_exact_name"),
("pinky03_R", "RPINKY03", "by_chain_index"),
("pinky02_R", "RPINKY02", "by_chain_index"),
("pinky01_R", "RPINKY01", "by_chain_index"),
("pinky00_R", "RPINKY00", "by_exact_name"),
("thumb03_L", "LTHUMB03", "by_chain_index"),
("thumb02_L", "LTHUMB02", "by_chain_index"),
("thumb01_L", "LTHUMB01", "by_chain_index"),
("index03_L", "LINDEX03", "by_chain_index"),
("index02_L", "LINDEX02", "by_chain_index"),
("index01_L", "LINDEX01", "by_chain_index"),
("index00_L", "LINDEX00", "by_exact_name"),
("middle03_L", "LMIDDLE03", "by_chain_index"),
("middle02_L", "LMIDDLE02", "by_chain_index"),
("middle01_L", "LMIDDLE01", "by_chain_index"),
("middle00_L", "LMIDDLE00", "by_exact_name"),
("ring03_L", "LRING03", "by_chain_index"),
("ring02_L", "LRING02", "by_chain_index"),
("ring01_L", "LRING01", "by_chain_index"),