forked from bioretics/ximage
-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathximage.py
1144 lines (969 loc) · 46.6 KB
/
ximage.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
#!/usr/bin/env python3
import argparse
import ast
import os
import pickle
import sys
from datetime import datetime
from hashlib import sha1
from string import Template
from uuid import UUID, uuid4
import cv2
import numpy as np
from libxmp import XMPFiles, XMPIterator, XMPMeta
XMP_NS_ALIQUIS = 'http://bioretics.com/aliquis'
XMPMeta.register_namespace(XMP_NS_ALIQUIS, 'aliquis')
__all__ = [ 'XImageMeta', 'XItem', 'XClass', 'XBlob', 'XImageParseError', 'XImageEmptyXMPError', 'ximread', 'ximwrite', 'ximage_main' ]
class XImageEmptyXMPError(Exception):
def __init__(self, file_path):
self.file_path = file_path
def __str__(self):
return 'empty XMP in file "%s"' % (self.file_path,)
class XImageParseError(Exception):
def __init__(self, tag_name):
self.tag_name = tag_name
def __str__(self):
return 'parsing tag "%s"' % (self.tag_name,)
class XImageMeta:
XMP_TEMPLATE = """<x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="Exempi + XMP Core 5.1.2">
<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#">
<rdf:Description rdf:about="" xmlns:aliquis="http://bioretics.com/aliquis">
<aliquis:acquisition>%(acquisition)s</aliquis:acquisition>
<aliquis:setup>%(setup)s</aliquis:setup>
<aliquis:classes>%(classes)s</aliquis:classes>
<aliquis:items>%(items)s</aliquis:items>
</rdf:Description>
</rdf:RDF>
</x:xmpmeta>"""
def __init__(self, classes, items=None, acquisition=None, setup=None):
self.classes = classes
self.items = [] if items is None else items
self.acquisition = {} if acquisition is None else acquisition
self.setup = {} if setup is None else setup
def get_colormap(self):
return [ c.color for c in self.classes ]
def to_xmp(self):
xmp = XMPMeta()
xmp.parse_from_str(str(self))
return xmp
def write(self, path):
xmpfile = XMPFiles(file_path=path, open_forupdate=True)
xmp = self.to_xmp()
xmpfile.put_xmp(xmp)
xmpfile.close_file()
@staticmethod
def read(path):
xmpfile = XMPFiles(file_path=path, open_forupdate=False)
xmp = xmpfile.get_xmp()
if xmp is None:
raise XImageEmptyXMPError(path)
return XImageMeta.parse(xmp)
@staticmethod
def parse(xmp_or_str):
if type(xmp_or_str) in [ str ] + ([ unicode ] if sys.version_info[0] == 2 else []):
xmp = XMPMeta()
xmp.parse_from_str(xmp_or_str)
else:
xmp = xmp_or_str
try:
tag = 'acquisition'
attribs = set([ x[1][8:] for x in XMPIterator(xmp, XMP_NS_ALIQUIS) if x[1].startswith('aliquis:') ])
acquisition = XImageMeta.parse_dict(xmp, tag) if '%s[1]' % (tag,) in attribs else {}
tag = 'setup'
setup = XImageMeta.parse_dict(xmp, tag) if '%s[1]' % (tag,) in attribs else {}
tag = 'classes'
classes = [ XClass.parse(xmp, '%s[%d]' % (tag, i)) for i in range(1, 1 + xmp.count_array_items(XMP_NS_ALIQUIS, tag)) ] if '%s[1]' % (tag,) in attribs else []
tag = 'items'
items = [ XItem.parse(xmp, '%s[%d]' % (tag, i)) for i in range(1, 1 + xmp.count_array_items(XMP_NS_ALIQUIS, tag)) ] if '%s[1]' % (tag,) in attribs else []
except:
raise XImageParseError(tag)
return XImageMeta(classes, items, acquisition, setup)
@staticmethod
def parse_value(xmp, prefix):
t = (xmp.get_property(XMP_NS_ALIQUIS, '%s/aliquis:type' % prefix)).lower()
if t.startswith('datetime'):
return xmp.get_property_datetime(XMP_NS_ALIQUIS, '%s/aliquis:value' % prefix)
y = xmp.get_property(XMP_NS_ALIQUIS, '%s/aliquis:value' % prefix)
if t.startswith('bool'):
y = bool(int(y))
elif t.startswith('int'):
y = int(y)
elif t.startswith('float'):
y = float(y)
return y
@staticmethod
def str_value(v):
if type(v) == bool:
t = 'boolean'
v = 1 if v else 0
elif type(v) == int:
t = 'integer'
elif type(v) == float:
t = 'float'
elif type(v) == datetime:
t = 'datetime'
v = v.strftime('%Y-%m-%dT%H:%M:%S')
else:
t = 'string'
return '<aliquis:type>%s</aliquis:type><aliquis:value>%s</aliquis:value>' % (t, str(v))
@staticmethod
def parse_list(xmp, prefix):
if xmp.does_property_exist(XMP_NS_ALIQUIS, prefix):
return [ XImageMeta.parse_value(xmp, '%s[%d]' % (prefix, i)) for i in range(1, 1 + xmp.count_array_items(XMP_NS_ALIQUIS, prefix)) ]
return []
@staticmethod
def str_list(l):
if len(l) == 0:
return ''
return '<rdf:Seq>%s</rdf:Seq>' % (''.join([ '<rdf:li rdf:parseType="Resource">%s</rdf:li>' % XImageMeta.str_value(x) for x in l ]))
@staticmethod
def parse_dict(xmp, prefix):
if xmp.does_property_exist(XMP_NS_ALIQUIS, prefix):
return { xmp.get_property(XMP_NS_ALIQUIS, '%s[%d]/aliquis:name' % (prefix, i)): XImageMeta.parse_value(xmp, '%s[%d]' % (prefix, i)) for i in range(1, 1 + xmp.count_array_items(XMP_NS_ALIQUIS, prefix)) }
return {}
@staticmethod
def str_dict(d):
if len(d) == 0:
return ''
return '<rdf:Bag>%s</rdf:Bag>' % (''.join([ '<rdf:li rdf:parseType="Resource"><aliquis:name>%s</aliquis:name>%s</rdf:li>' % (k, XImageMeta.str_value(v)) for k, v in d.items() ]))
def __str__(self):
acquisition_str = XImageMeta.str_dict(self.acquisition)
setup_str = XImageMeta.str_dict(self.setup)
classes_str = '<rdf:Seq>%s</rdf:Seq>' % (''.join([ '<rdf:li rdf:parseType="Resource">%s</rdf:li>' % str(c) for c in self.classes ]))
items_str = '<rdf:Bag>%s</rdf:Bag>' % (''.join([ '<rdf:li rdf:parseType="Resource">%s</rdf:li>' % str(item) for item in self.items ])) if len(self.items) > 0 else ''
return XImageMeta.XMP_TEMPLATE % { 'acquisition': acquisition_str, 'setup': setup_str, 'classes': classes_str, 'items': items_str }
class XItem:
XMP_TEMPLATE = '<aliquis:uuid>%(uuid)s</aliquis:uuid><aliquis:blobs><rdf:Bag>%(blobs)s</rdf:Bag></aliquis:blobs>'
def __init__(self, blobs, uuid=None):
assert len(blobs) > 0, 'An item must contain at least one blob'
self.blobs = blobs
self.uuid = uuid4() if uuid is None else uuid
@staticmethod
def parse(xmp, prefix):
uuid = UUID(xmp.get_property(XMP_NS_ALIQUIS, '%s/aliquis:uuid' % prefix))
blobs = [ XBlob.parse(xmp, '%s/aliquis:blobs[%d]' % (prefix, i)) for i in range(1, 1 + xmp.count_array_items(XMP_NS_ALIQUIS, '%s/aliquis:blobs' % prefix)) ]
return XItem(blobs, uuid)
def __str__(self):
return XItem.XMP_TEMPLATE % { 'uuid': str(self.uuid), 'blobs': ''.join([ '<rdf:li rdf:parseType="Resource">%s</rdf:li>' % str(blob) for blob in self.blobs ]) }
class XClass:
XMP_TEMPLATE = '<aliquis:name>%(name)s</aliquis:name><aliquis:color>%(color)s</aliquis:color>'
def __init__(self, name, color=None, remap=None):
self.name = name
self.color = color or XClass.get_random_color()
self.remap = remap
@staticmethod
def get_random_color():
return tuple(np.random.randint(0, 256, 3).tolist())
@staticmethod
def parse(xmp, prefix):
name = xmp.get_property(XMP_NS_ALIQUIS, '%s/aliquis:name' % prefix)
color = tuple(map(int, xmp.get_property(XMP_NS_ALIQUIS, '%s/aliquis:color' % prefix).split(',')))
try:
remap = int(xmp.get_property(XMP_NS_ALIQUIS, '%s/aliquis:remap' % prefix))
except:
remap = None
return XClass(name, color, remap)
def __eq__(self, other):
return self.name == other.name and self.color == other.color and self.remap == other.remap
def __str__(self):
s = XClass.XMP_TEMPLATE % { 'name': str(self.name), 'color': ','.join(map(str, self.color)) }
if self.remap is not None:
s += '<aliquis:remap>%d</aliquis:remap>' % self.remap
return s
class XBlob:
XMP_TEMPLATE = '<aliquis:values>%(values)s</aliquis:values><aliquis:points>%(points)s</aliquis:points>%(blobs)s'
def __init__(self, points, values, children=None):
self.points = points
self.values = values
self.children = [] if children is None else children
def get_classid(self):
return np.argmax(self.values)
def get_contour_area(self):
return float(cv2.contourArea(self.points))
def get_area(self):
# Using masks is (far) more accurate
return self.get_contour_area() - sum([ b.get_contour_area() for b in self.children ])
def draw(self, im, colormap, filled=False):
classid = self.get_classid()
color_alpha = colormap[classid]
color = tuple(color_alpha[:3])
if filled:
if len(color_alpha) == 4:
overlay = im.copy()
alpha = color_alpha[3] / 255.0
cv2.fillPoly(overlay, [ self.points ], color)
cv2.addWeighted(overlay, alpha, im, 1 - alpha, 0, im)
else:
cv2.fillPoly(im, [ self.points ], color)
else:
cv2.drawContours(im, [ self.points ], 0, color)
for blob in self.children:
blob.draw(im, colormap, filled)
return im
def get_mask(self, shape, dtype=np.uint8):
mask = np.zeros(shape, dtype=dtype)
return self.draw(mask, { self.get_classid(): (1,) }, True)
def get_mask_like(self, im):
return self.get_mask(im.shape, im.dtype)
@staticmethod
def parse(xmp, prefix):
points = np.int32(list(map(int, xmp.get_property(XMP_NS_ALIQUIS, '%s/aliquis:points' % prefix).split(','))))
values = np.float32(list(map(float, xmp.get_property(XMP_NS_ALIQUIS, '%s/aliquis:values' % prefix).split(','))))
if xmp.does_property_exist(XMP_NS_ALIQUIS, '%s/aliquis:blobs' % prefix):
children = [ XBlob.parse(xmp, '%s/aliquis:blobs[%d]' % (prefix, i)) for i in range(1, 1 + xmp.count_array_items(XMP_NS_ALIQUIS, '%s/aliquis:blobs' % prefix)) ]
else:
children = []
return XBlob(points.reshape(len(points) // 2, 2), values, children)
def __str__(self):
values_str = ','.join(map(str, self.values))
points_str = ','.join(map(str, self.points.flatten()))
children_str = '<aliquis:blobs><rdf:Bag>%s</rdf:Bag></aliquis:blobs>' % (''.join([ '<rdf:li rdf:parseType="Resource">%s</rdf:li>' % str(child) for child in self.children ]))
return XBlob.XMP_TEMPLATE % { 'values': values_str, 'points': points_str, 'blobs': children_str if len(self.children) > 0 else '' }
def ximread(path):
im = cv2.imread(path, -1)
assert im is not None, 'Image data missing'
meta = XImageMeta.read(path)
return im, meta
def ximwrite(path, im, meta):
cv2.imwrite(path, im)
meta.write(path)
################################################################################
# XImage utility functions #####################################################
################################################################################
def ximage_inject(args):
with open(args.metadata, 'r') as f:
m = XImageMeta.parse(f.read())
m.write(args.path)
return 0
def ximage_extract(args):
print(str(XImageMeta.read(args.path)))
return 0
def ximage_uuid(args):
meta = XImageMeta.read(args.path)
sorted_items = sorted(meta.items, key=lambda item: np.vstack([ b.points for b in item.blobs ]).mean(axis=0).round().astype(int).tolist())
if len(args.uuids) == 0:
for item in sorted_items:
print(str(item.uuid))
else:
assert len(args.uuids) == len(sorted_items), 'UUIDs must be %d' % (len(sorted_items),)
for uuid, item in zip(args.uuids, sorted_items):
if uuid == '0':
continue
item.uuid = UUID(uuid)
meta.write(args.path)
return 0
def ximage_import(args):
def versor(d, shape, dtype=np.float32):
v = np.zeros(shape, dtype=dtype)
v[d] = 1
return v
def contour_level(hier, i, l=0):
*_, parent = hier[i]
if parent == -1:
return l
return contour_level(hier, parent, l + 1)
def blob_init_data(blob, template_mask):
mask = blob.get_mask_like(template_mask)
return (mask, float(np.count_nonzero(mask)))
def all_subblobs(blob, blobs, blobs_data, overlap_ratio_threshold):
subblobs = []
blob_mask, _ = blobs_data[blob]
for b in blobs - set([ blob ]):
if np.all(blobs_data[b][0] * blob_mask == blobs_data[b][0]):
subblobs.append(b)
return set(subblobs)
def blob_descendents(blobs_subblobs, blob):
descendents = subblobs = blobs_subblobs[blob]
for b in subblobs:
descendents = descendents.union(blob_descendents(blobs_subblobs, b))
return descendents
def build_hierarchy(blobs_children, parent):
# Find and remove roots from graph edges
roots = set(blobs_children.keys()) - set([ x for xs in blobs_children.values() for x in xs ])
for root in roots:
blobs_children.pop(root)
# Recursive step
for root in roots:
parent.children.append(root)
build_hierarchy(blobs_children, root)
mask = cv2.imread(args.mask, -1)
# Count number of classes
classes_count = len(np.trim_zeros(np.bincount(mask.flatten())[:-1], 'b')) - 1
if len(args.classes) > 0:
classes = list(map(XClass, args.classes))
else:
classes = [ XClass(str(i)) for i in range(classes_count) ]
classes_num = len(classes)
assert classes_num >= classes_count, 'Classes must be at least %d' % (classes_count)
for xc, color in zip(classes, args.colors):
try:
xc.color = _COLORS[color]
except KeyError:
color = color.strip()[2:]
xc.color = tuple([ int(color[i:(i + 2)], 16) for i in range(0, 6, 2) ])
default_class = 0
overlap_ratio_threshold = 0.9
default_value = versor(default_class, classes_num)
ret = cv2.findContours(np.pad(mask != 255, 1, 'constant', constant_values=0).astype(np.uint8), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
contours = ret[-2]
items = [ XItem([ XBlob(contour.squeeze(1) - 1, default_value) ]) for contour in contours ]
# Find items subblobs
for item in items:
item_blob = item.blobs[0]
item_mask = item_blob.get_mask_like(mask)
# Find all subblobs inside the item
blobs = set()
item_indexmask = item_mask * mask
for c in range(classes_num):
if c == default_class:
continue
ret = cv2.findContours((item_indexmask == c).astype(np.uint8), cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)
contours = ret[-2]
hier = ret[-1]
# Blobs are only even levels (contours hierarchy alternate full and empty areas)
blobs = blobs.union(set([ XBlob(contour.squeeze(1), versor(c, classes_num)) for i, contour in enumerate(contours) if contour_level(hier[0], i) % 2 == 0 ]))
# b: (mask, area)
blobs_data = { b: blob_init_data(b, mask) for b in blobs }
# b: [ blobs contained in b ]
blobs_subblobs = { b: all_subblobs(b, blobs, blobs_data, overlap_ratio_threshold) for b in blobs }
# b: [ b's children ]
blobs_children = { b: subblobs - reduce(set.union, [ blob_descendents(blobs_subblobs, x) for x in subblobs ], set()) for b, subblobs in blobs_subblobs.items() }
# Reconstruct blobs hierarchy for the item
item_blob.children = list(blobs - reduce(set.union, blobs_children.values(), set()))
for blob in blobs:
blob.children = list(blobs_children[blob])
for item, uuid in zip(items, args.uuids):
if uuid == '0':
continue
item.uuid = UUID(uuid)
im_meta = XImageMeta(classes, items)
im_meta.write(args.path)
return 0
def ximage_export(args):
im, im_meta = ximread(args.path)
colormap = { i: (i if c.remap is None else c.remap,) for i, c in enumerate(im_meta.classes) }
mask = np.full(im.shape[:2], 255, dtype=np.uint8)
for item in im_meta.items:
for blob in item.blobs:
blob.draw(mask, colormap, True)
cv2.imwrite(args.mask, mask)
return 0
def ximage_update(args):
im_path = args.path
overwrite = args.overwrite
im_meta = XImageMeta.read(im_path)
mapping = dict([ kv.split('=') for kvs in args.mapping for kv in kvs.split() ])
with open(args.metadata, 'r') as f:
im_meta_update = XImageMeta.parse(Template(f.read()).substitute(mapping))
if args.replace_classes:
im_meta.classes = im_meta_update.classes
else:
classes = im_meta.classes
classes_num = len(classes)
classes_update = im_meta_update.classes
if classes_num == 0 or (len(classes_update) >= classes_num and all([ c.name == cu.name for c, cu in zip(classes, classes_update) ])):
if overwrite:
for c, cu in zip(classes, classes_update):
c.color = cu.color
classes.extend(classes_update[classes_num:])
acquisition = im_meta.acquisition
for a_name, a in im_meta_update.acquisition.items():
if overwrite or (a_name not in acquisition):
acquisition[a_name] = a
setup = im_meta.setup
for s_name, s in im_meta_update.setup.items():
if overwrite or (s_name not in setup):
setup[s_name] = s
im_meta.write(im_path)
def ximage_view(args):
im_path = args.path
if args.metadata:
with open(args.metadata, 'r') as f:
im_meta = XImageMeta.parse(f.read())
else:
im_meta = XImageMeta.read(im_path)
items = im_meta.items
colormap = im_meta.get_colormap()
# Display infos on terminal
sys.stderr.write('Acquisition parameters:\n')
for k, v in sorted(im_meta.acquisition.items()):
sys.stderr.write('- %s: %s\n' % (k, str(v)))
sys.stderr.write('Setup parameters:\n')
for k, v in sorted(im_meta.setup.items()):
sys.stderr.write('- %s: %s\n' % (k, str(v)))
sys.stderr.write('Image contain %d item%s.\n' % (len(items), 's' if len(items) != 1 else ''))
# Debug draw (if image available)
im = cv2.imread(im_path, -1) if im_path is not None else None
if im is not None:
# Create debug image as a color copy of im
im_debug = np.zeros(im.shape[:2] + (3,), dtype=np.uint8)
if im.ndim == 2:
im_debug[:, :, 0] = im_debug[:, :, 1] = im_debug[:, :, 2] = im
else:
im_debug[:, :, :3] = im[:, :, :3]
# Draw items blobs
for item in items:
for blob in item.blobs:
blob.draw(im_debug, colormap)
uuid_text = str(item.uuid)
(uuid_w, uuid_h), uuid_baseline = cv2.getTextSize(uuid_text, cv2.FONT_HERSHEY_SIMPLEX, 0.5, 1)
blob_topleft = blob.points.min(axis=0).round().astype(int)
blob_y = blob_topleft[1] - uuid_h + uuid_baseline - 4
if blob_y < 4:
blob_bottomright = blob.points.max(axis=0).round().astype(int)
blob_y = blob_bottomright[1] + uuid_h + uuid_baseline + 4
blob_center = blob.points.mean(axis=0).round().astype(int)
cv2.putText(im_debug, uuid_text, (blob_center[0] - uuid_w // 2, blob_y), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0xff, 0xff, 0xff))
# Write infos on debug image
x = 15
for class_id, xclass in enumerate(im_meta.classes):
class_color = xclass.color
y = (class_id + 1) * 25
cv2.line(im_debug, (x, y - 5), (x + 20, y - 5), class_color)
cv2.putText(im_debug, xclass.name, (x + 30, y), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0xff, 0xff, 0xff))
else:
im_debug = None
if im_debug is not None:
if args.output_path is None:
cv2.imshow(im_path, im_debug)
cv2.waitKey(0)
else:
cv2.imwrite(args.output_path, im_debug)
return 0
class XValue:
def __init__(self, val):
self.val = val
@staticmethod
def parse(buf):
return pickle.loads(str(buf))
def __str__(self):
return str(self.val)
def _ximage_index_connect(args, create=False):
import sqlite3
# Custom database types converters and adapters
sqlite3.register_converter('xvalue', XValue.parse)
sqlite3.register_converter('color', lambda buf: tuple(np.frombuffer(buf, dtype='|u1').tolist()))
sqlite3.register_converter('vector', lambda buf: np.frombuffer(buf, dtype='<f4'))
sqlite3.register_converter('points', lambda buf: np.frombuffer(buf, dtype='<i4').reshape(len(buf) / 8, 2))
sqlite3.register_converter('uuid', lambda buf: UUID(bytes=buf))
sqlite3.register_adapter(XValue, lambda x: pickle.dumps(x.val))
sqlite3.register_adapter(np.ndarray, lambda a: np.getbuffer(a))
sqlite3.register_adapter(UUID, lambda uuid: buffer(uuid.get_bytes()))
index_path = os.path.join(args.root, '.ximage-index.db')
if not create:
# Try to open existing database path (raise IOError)
with open(index_path, 'r') as f:
pass
conn = sqlite3.connect(index_path, detect_types=sqlite3.PARSE_DECLTYPES)
conn.create_function('xvalue_parse', 1, XValue.parse)
return conn
def _ximage_index_insert_blobs(cur, blob, classes, xbelonging_id, parent_id=None):
cid = blob.get_classid()
c = classes[cid]
(xclass_id,) = cur.execute('SELECT id FROM XClass WHERE classid=? AND name=? AND color=?', (cid, c.name, np.array(c.color, dtype=np.uint8))).fetchone()
cur.execute('INSERT OR REPLACE INTO XBlob(xbelonging_id, parent_id, xclass_id, val, area, vals, contour) VALUES(?, ?, ?, ?, ?, ?, ?)', (xbelonging_id, parent_id, xclass_id, float(blob.values[cid]), blob.get_area(), blob.values, blob.points))
blob_id = cur.lastrowid
for b in blob.children:
_ximage_index_insert_blobs(cur, b, classes, xbelonging_id, blob_id)
def ximage_index(args):
TABLES_SEARCH = [ 'XBlob', 'XItem', 'XBelonging', 'XImage', 'XClass', 'XImageParam' ]
IMAGES_EXTS = [ '.png', '.tif', '.tiff', '.jpg', '.jpeg' ]
root = os.path.realpath(args.root)
try:
conn = _ximage_index_connect(args, True)
except ImportError:
sys.stderr.write('Error: cannot import sqlite3 module\n')
return -1
cur = conn.cursor()
cur.execute('SELECT * FROM sqlite_master WHERE type="table" AND name IN (%s);' % (','.join(map(repr, TABLES_SEARCH)),))
if len(cur.fetchall()) != len(TABLES_SEARCH):
cur.executescript(_XIMAGE_INDEX_CREATE_SCHEMA)
conn.commit()
ims_ids = {}
for root_path, _, filenames in os.walk(root):
for im_filename in filter(lambda f: os.path.splitext(f)[1].lower() in IMAGES_EXTS, filenames):
im_path = os.path.realpath(os.path.join(root_path, im_filename))
im_relpath = os.path.relpath(im_path, root)
try:
im, im_meta = ximread(im_path)
im.flags.writeable = False
im_id = UUID(bytes=sha1(im.data).digest()[:16], version=4)
try:
sys.stderr.write('Error: inserting %s: duplicate image (%s)\n' % (im_relpath, ims_ids[im_id]))
continue
except KeyError:
pass
# Update XClasses
for i, c in enumerate(im_meta.classes):
cur.execute('INSERT OR IGNORE INTO XClass(classid, name, color) VALUES(?, ?, ?)', (i, c.name, np.array(c.color, dtype=np.uint8)))
conn.commit()
# Update Acquisition
for name, val in im_meta.acquisition.items():
cur.execute('INSERT OR IGNORE INTO XImageParam(ximage_id, param_type, name, val) VALUES(?, 0, ?, ?)', (im_id, name, XValue(val)))
conn.commit()
# Update Setup
for name, val in im_meta.setup.items():
cur.execute('INSERT OR IGNORE INTO XImageParam(ximage_id, param_type, name, val) VALUES(?, 1, ?, ?)', (im_id, name, XValue(val)))
conn.commit()
# Insert XImage
cur.execute('INSERT OR REPLACE INTO XImage(id, path) VALUES(?, ?)', (im_id, im_relpath))
# Insert XItems
for item in im_meta.items:
cur.execute('INSERT OR REPLACE INTO XItem(id) VALUES(?)', (item.uuid,))
cur.execute('INSERT OR REPLACE INTO XBelonging(ximage_id, xitem_id) VALUES(?, ?)', (im_id, item.uuid))
xbelonging_id = cur.lastrowid
for blob in item.blobs:
_ximage_index_insert_blobs(cur, blob, im_meta.classes, xbelonging_id)
# Commit insert
conn.commit()
sys.stderr.write('Done %s\n' % (im_relpath,))
ims_ids[im_id] = im_relpath
except Exception as e:
sys.stderr.write('Error: inserting %s: %s\n' % (im_relpath, str(e)))
return 0
def ximage_stats(args):
try:
conn = _ximage_index_connect(args)
except IOError as e:
sys.stderr.write('Error: cannot open index: %s\n' % (str(e),))
return 1
except ImportError:
sys.stderr.write('Error: cannot import sqlite3 module\n')
return -1
cur = conn.cursor()
xclasses = cur.execute('SELECT classid, name FROM XClass;').fetchall()
(ximages_num,) = cur.execute('SELECT COUNT(*) FROM XImage;').fetchone()
(ximages_empty_num,) = cur.execute('SELECT COUNT(*) FROM (SELECT COUNT(*) AS count, XImage.id FROM XImage, XBelonging WHERE XImage.id=XBelonging.ximage_id GROUP BY XImage.id HAVING count=0);').fetchone()
(xitems_num,) = cur.execute('SELECT COUNT(*) FROM XItem;').fetchone()
(xblobs_num,) = cur.execute('SELECT COUNT(*) FROM XBlob;').fetchone()
print('Total classes: %d%s' % (len(xclasses), ' (%s)' % (', '.join([ '%d: %s' % c for c in xclasses ])) if len(xclasses) > 0 else ''))
print('Total images: %d (%d empty)' % (ximages_num, ximages_empty_num))
print('Total items: %d' % xitems_num)
print('Total blobs: %d' % xblobs_num)
try:
(avg_items_per_image,) = cur.execute('SELECT AVG(count) FROM (SELECT COUNT(*) AS count, XImage.id FROM XImage, XBelonging WHERE XImage.id=XBelonging.ximage_id GROUP BY XImage.id);').fetchone()
(min_items_per_image, _, min_items_per_image_path) = cur.execute('SELECT COUNT(*) AS count, XImage.id, path FROM XImage, XBelonging WHERE XImage.id=XBelonging.ximage_id GROUP BY XImage.id ORDER BY count ASC LIMIT 1;').fetchone()
(max_items_per_image, _, max_items_per_image_path) = cur.execute('SELECT COUNT(*) AS count, XImage.id, path FROM XImage, XBelonging WHERE XImage.id=XBelonging.ximage_id GROUP BY XImage.id ORDER BY count DESC LIMIT 1;').fetchone()
print('Items per image:\n Minimum: %d (%s)\n Maximum: %d (%s)\n Average: %.1f' % (min_items_per_image, min_items_per_image_path, max_items_per_image, max_items_per_image_path, round(avg_items_per_image, 1)))
except ValueError:
print('No items found')
try:
(avg_blobs_per_item,) = cur.execute('SELECT AVG(count) FROM (SELECT COUNT(*) AS count, XBelonging.xitem_id FROM XBlob, XBelonging, XImage WHERE XImage.id=XBelonging.ximage_id AND XBelonging.id=XBlob.xbelonging_id GROUP BY XBelonging.xitem_id);').fetchone()
(min_blobs_per_item, min_blobs_per_item_uuid) = cur.execute('SELECT COUNT(*) AS count, XBelonging.xitem_id FROM XBlob, XBelonging, XImage WHERE XImage.id=XBelonging.ximage_id AND XBelonging.id=XBlob.xbelonging_id GROUP BY XBelonging.xitem_id ORDER BY count ASC LIMIT 1;').fetchone()
(max_blobs_per_item, max_blobs_per_item_uuid) = cur.execute('SELECT COUNT(*) AS count, XBelonging.xitem_id FROM XBlob, XBelonging, XImage WHERE XImage.id=XBelonging.ximage_id AND XBelonging.id=XBlob.xbelonging_id GROUP BY XBelonging.xitem_id ORDER BY count DESC LIMIT 1;').fetchone()
(avg_blobs_per_image,) = cur.execute('SELECT AVG(count) FROM (SELECT COUNT(*) AS count, XImage.id FROM XBlob, XBelonging, XImage WHERE XImage.id=XBelonging.ximage_id AND XBelonging.id=XBlob.xbelonging_id GROUP BY XImage.id);').fetchone()
(min_blobs_per_image, _, min_blobs_per_image_path) = cur.execute('SELECT COUNT(*) AS count, XImage.id, path FROM XBlob, XBelonging, XImage WHERE XImage.id=XBelonging.ximage_id AND XBelonging.id=XBlob.xbelonging_id GROUP BY XImage.id ORDER BY count ASC LIMIT 1;').fetchone()
(max_blobs_per_image, _, max_blobs_per_image_path) = cur.execute('SELECT COUNT(*) AS count, XImage.id, path FROM XBlob, XBelonging, XImage WHERE XImage.id=XBelonging.ximage_id AND XBelonging.id=XBlob.xbelonging_id GROUP BY XImage.id ORDER BY count DESC LIMIT 1;').fetchone()
(xblob_minarea, xblob_minarea_path) = cur.execute('SELECT area, path FROM XBlob, XBelonging, XImage WHERE XImage.id=XBelonging.ximage_id AND XBelonging.id=XBlob.xbelonging_id ORDER BY area ASC LIMIT 1;').fetchone()
(xblob_maxarea, xblob_maxarea_path) = cur.execute('SELECT area, path FROM XBlob, XBelonging, XImage WHERE XImage.id=XBelonging.ximage_id AND XBelonging.id=XBlob.xbelonging_id ORDER BY area DESC LIMIT 1;').fetchone()
(xblob_avgarea,) = cur.execute('SELECT AVG(area) FROM XBlob, XBelonging, XImage WHERE XImage.id=XBelonging.ximage_id AND XBelonging.id=XBlob.xbelonging_id;').fetchone()
print('Blobs per item:\n Minimum: %d (%s)\n Maximum: %d (%s)\n Average: %.1f' % (min_blobs_per_item, str(min_blobs_per_item_uuid), max_blobs_per_item, str(max_blobs_per_item_uuid), round(avg_blobs_per_item, 1)))
print('Blobs per image:\n Minimum: %d (%s)\n Maximum: %d (%s)\n Average: %.1f' % (min_blobs_per_image, min_blobs_per_image_path, max_blobs_per_image, max_blobs_per_image_path, round(avg_blobs_per_image, 1)))
print('Blobs areas:\n Minimum: %dpx (%s)\n Maximum: %dpx (%s)\n Average: %dpx' % (xblob_minarea, xblob_minarea_path, xblob_maxarea, xblob_maxarea_path, xblob_avgarea))
except ValueError:
print('No blobs found')
def ximage_query(args):
class XEvalContext:
def __init__(self, cur):
self.cur = cur
self.cur.execute('SELECT path FROM XImage;')
self.all_paths = self._fetch_all()
self.reset()
def push_param(self, p):
n = 'x%d' % (len(self.params),)
self.params[n] = p
return ':%s' % (n,)
def execute_query(self):
from_clause = ', '.join(self.from_tables)
where_clause = ' AND '.join(self.where_conjs)
groupby_clause = '' if len(self.having_conjs) == 0 else ' GROUP BY path HAVING %s' % (' AND '.join(self.having_conjs),)
query = 'SELECT path FROM %s WHERE %s%s;' % (from_clause, where_clause, groupby_clause)
self.cur.execute(query, self.params)
return self._fetch_all()
def reset(self):
self.params = {}
self.where_conjs = set()
self.from_tables = set()
self.having_conjs = set()
def _fetch_all(self):
return set([ r[0] for r in self.cur.fetchall() ])
def xeval_num(node):
return node.n
def xeval_str(node):
return node.s
def xeval_attribute(node, ctx):
assert type(node.value) == ast.Name
t = node.value.id.capitalize()
if t in [ 'Acquisition', 'Setup' ]:
ctx.from_tables.update([ 'XImage', 'XImageParam AS Acquisition', 'XImageParam AS Setup' ])
ctx.where_conjs.update([ 'Acquisition.param_type=0', 'Acquisition.ximage_id=XImage.id', 'Setup.param_type=1', 'Setup.ximage_id=XImage.id' ])
ctx.where_conjs.add('%s.name=%s' % (t, ctx.push_param(node.attr)))
return 'xvalue_parse(%s.val)' % (t,)
elif t == 'Item':
ctx.from_tables.update([ 'XImage', 'XBelonging', 'XBlob', 'XClass' ])
ctx.where_conjs.update([ 'XImage.id=XBelonging.ximage_id', 'XBlob.xbelonging_id=XBelonging.id', 'XBlob.xclass_id=XClass.id' ])
ctx.where_conjs.add('XClass.name=%s' % (ctx.push_param(node.attr),))
return '*'
else:
pass # raise
def xeval_call(node, ctx):
fn = node.func.id.lower()
if fn == 'count':
assert len(node.args) == 1 and type(node.args[0]) == ast.Attribute
return True, 'COUNT(%s)' % (xeval_attribute(node.args[0], ctx),)
elif fn == 'area':
assert len(node.args) == 1 and type(node.args[0]) == ast.Attribute
xeval_attribute(node.args[0], ctx)
return True, 'XBlob.area'
elif fn == 'areas':
assert len(node.args) == 1 and type(node.args[0]) == ast.Attribute
xeval_attribute(node.args[0], ctx)
return True, 'SUM(XBlob.area)'
else:
pass # Raise
def xeval_unaryop(node, ctx):
if type(node.op) == ast.Not:
return ctx.all_paths - xeval(node.operand, cur)
else:
pass # Raise
def xeval_boolop(node, ctx):
values = [ xeval(v, ctx) for v in node.values ]
if type(node.op) == ast.And:
return reduce(set.intersection, values, ctx.all_paths)
elif type(node.op) == ast.Or:
return reduce(set.union, values, set())
else:
pass # Raise
def xeval_compare(node, ctx):
comparators = [ node.left ] + node.comparators
paths = ctx.all_paths
for op, x, y in zip(map(type, node.ops), comparators[:-1], comparators[1:]):
if op == ast.Lt:
op_str = '<'
elif op == ast.LtE:
op_str = '<='
elif op == ast.Gt:
op_str = '>'
elif op == ast.GtE:
op_str = '>='
elif op == ast.Eq:
op_str = '='
elif op == ast.NotEq:
op_str = '<>'
else:
pass # raise
comps = [ '', '' ]
conjs = ctx.where_conjs
for i, z in enumerate([ x, y ]):
if type(z) == ast.Call:
h, comps[i] = xeval_call(z, ctx)
if h:
conjs = ctx.having_conjs
elif type(z) == ast.Attribute:
comps[i] = xeval_attribute(z, ctx)
elif type(z) == ast.Str:
comps[i] = ctx.push_param(xeval_str(z))
elif type(z) == ast.Num:
comps[i] = ctx.push_param(xeval_num(z))
else:
pass # raise
conjs.add('%s%s%s' % (comps[0], op_str, comps[1]))
paths = paths.intersection(ctx.execute_query())
ctx.reset()
if len(paths) == 0:
break
return paths
def xeval(node, ctx):
if type(node) == ast.UnaryOp:
return xeval_unaryop(node, ctx)
elif type(node) == ast.BoolOp:
return xeval_boolop(node, ctx)
elif type(node) == ast.Compare:
return xeval_compare(node, ctx)
else:
pass # raise
try:
conn = _ximage_index_connect(args)
except IOError as e:
sys.stderr.write('Error: cannot open index: %s\n' % (str(e),))
return 1
except ImportError:
sys.stderr.write('Error: cannot import sqlite3 module\n')
return -1
query = ' '.join(args.query)
if query is None or len(query.strip()) == 0:
paths = XEvalContext(conn.cursor()).all_paths
else:
root = ast.parse(query, '<query>', 'eval')
paths = xeval(root.body, XEvalContext(conn.cursor()))
print('\n'.join(sorted(paths)))
return 0
def ximage_main(prog_name='ximage'):
parser = argparse.ArgumentParser(prog=prog_name, description='Manipulate images along with its metadata')
subparsers = parser.add_subparsers(help='sub-commands help')
parser_import = subparsers.add_parser('import', help='Add blobs and metadata to an image, importing index mask')
parser_import.add_argument('-K', '--classes', type=str, required=False, nargs='+', default=[], help='List of classes, 0-indexed')
parser_import.add_argument('-U', '--uuids', type=str, required=False, nargs='+', default=[], help='List of UUIDs (0 to generate)')
parser_import.add_argument('-C', '--colors', type=str, required=False, nargs='+', default=[], help='List of classes\' colors')
parser_import.add_argument('mask', type=str, help='Index mask path')
parser_import.add_argument('path', type=str, help='Image path')
parser_import.set_defaults(func=ximage_import)
parser_export = subparsers.add_parser('export', help='Export index mask from an image')
parser_export.add_argument('path', type=str, help='Image path')
parser_export.add_argument('mask', type=str, help='Index mask path')
parser_export.set_defaults(func=ximage_export)
parser_inject = subparsers.add_parser('inject', help='Add blobs and metadata to an image')
parser_inject.add_argument('metadata', type=str, help='XML')
parser_inject.add_argument('path', type=str, help='Image path')
parser_inject.set_defaults(func=ximage_inject)
parser_extract = subparsers.add_parser('extract', help='Extract blobs and metadata from an image')
parser_extract.add_argument('path', type=str, help='Image path')
parser_extract.set_defaults(func=ximage_extract)
parser_update = subparsers.add_parser('update', help='Update image metadata with XML')
parser_update.add_argument('-f', '--overwrite', action='store_true', required=False, default=False, help='Overwrite present values (default: no)')
parser_update.add_argument('-K', '--replace-classes', action='store_true', required=False, default=False, help='Overwrite all defined classes (default: no)')
parser_update.add_argument('metadata', type=str, help='Metadata to update with')
parser_update.add_argument('path', type=str, help='Image path')
parser_update.add_argument('mapping', nargs=argparse.REMAINDER)
parser_update.set_defaults(func=ximage_update)
parser_uuid = subparsers.add_parser('uuid', help='Get/set items UUIDs (left to right, top to bottom)')
parser_uuid.add_argument('-U', '--uuids', type=str, required=False, nargs='+', default=[], help='List of new UUIDs (0 to skip)')
parser_uuid.add_argument('path', type=str, help='Image path')
parser_uuid.set_defaults(func=ximage_uuid)
parser_view = subparsers.add_parser('view', help='View images, blobs and other metadata')
parser_view.add_argument('-m', '--metadata', type=str, required=False, default=None, help='Use this XML instead of image\'s XMP')
parser_view.add_argument('-o', '--output_path', type=str, required=False, default=None, help='Output image path')
parser_view.add_argument('path', type=str, help='Image path')
parser_view.set_defaults(func=ximage_view)
parser_index = subparsers.add_parser('index', help='Index a directory (recursively) of XImages')
parser_index.add_argument('root', type=str, help='Root directory path')
parser_index.set_defaults(func=ximage_index)
parser_query = subparsers.add_parser('query', help='Query on indexed directory of XImages')
parser_query.add_argument('-D', '--root', type=str, required=False, default=os.getcwd(), help='Root directory path (default: cwd)')
parser_query.add_argument('query', nargs=argparse.REMAINDER)
parser_query.set_defaults(func=ximage_query)
parser_stats = subparsers.add_parser('stats', help='Show some indexed directory statistics')
parser_stats.add_argument('-D', '--root', type=str, required=False, default=os.getcwd(), help='Root directory path (default: cwd)')
parser_stats.set_defaults(func=ximage_stats)
args = parser.parse_args()
sys.exit(args.func(args))
_COLORS = dict(
maroon=(0x00, 0x00, 0x80),
darkred=(0x00, 0x00, 0x8b),
red=(0x00, 0x00, 0xff),
lightpink=(0xc1, 0xb6, 0xff),
crimson=(0x3c, 0x14, 0xdc),
palevioletred=(0x93, 0x70, 0xdb),
hotpink=(0xb4, 0x69, 0xff),
deeppink=(0x93, 0x14, 0xff),
mediumvioletred=(0x85, 0x15, 0xc7),
purple=(0x80, 0x00, 0x80),
darkmagenta=(0x8b, 0x00, 0x8b),
orchid=(0xd6, 0x70, 0xda),
thistle=(0xd8, 0xbf, 0xd8),
plum=(0xdd, 0xa0, 0xdd),
violet=(0xee, 0x82, 0xee),
fuchsia=(0xff, 0x00, 0xff),
magenta=(0xff, 0x00, 0xff),
mediumorchid=(0xd3, 0x55, 0xba),
darkviolet=(0xd3, 0x00, 0x94),
darkorchid=(0xcc, 0x32, 0x99),
blueviolet=(0xe2, 0x2b, 0x8a),
indigo=(0x82, 0x00, 0x4b),
mediumpurple=(0xdb, 0x70, 0x93),
slateblue=(0xcd, 0x5a, 0x6a),
mediumslateblue=(0xee, 0x68, 0x7b),
darkblue=(0x8b, 0x00, 0x00),
mediumblue=(0xcd, 0x00, 0x00),
blue=(0xff, 0x00, 0x00),
navy=(0x80, 0x00, 0x00),
midnightblue=(0x70, 0x19, 0x19),
darkslateblue=(0x8b, 0x3d, 0x48),
royalblue=(0xe1, 0x69, 0x41),
cornflowerblue=(0xed, 0x95, 0x64),
lightsteelblue=(0xde, 0xc4, 0xb0),
aliceblue=(0xff, 0xf8, 0xf0),
ghostwhite=(0xff, 0xf8, 0xf8),
lavender=(0xfa, 0xe6, 0xe6),
dodgerblue=(0xff, 0x90, 0x1e),
steelblue=(0xb4, 0x82, 0x46),
deepskyblue=(0xff, 0xbf, 0x00),
slategray=(0x90, 0x80, 0x70),
lightslategray=(0x99, 0x88, 0x77),
lightskyblue=(0xfa, 0xce, 0x87),
skyblue=(0xeb, 0xce, 0x87),
lightblue=(0xe6, 0xd8, 0xad),
teal=(0x80, 0x80, 0x00),
darkcyan=(0x8b, 0x8b, 0x00),
darkturquoise=(0xd1, 0xce, 0x00),
cyan=(0xff, 0xff, 0x00),
mediumturquoise=(0xcc, 0xd1, 0x48),
cadetblue=(0xa0, 0x9e, 0x5f),
paleturquoise=(0xee, 0xee, 0xaf),
lightcyan=(0xff, 0xff, 0xe0),
azure=(0xff, 0xff, 0xf0),
lightseagreen=(0xaa, 0xb2, 0x20),
turquoise=(0xd0, 0xe0, 0x40),
powderblue=(0xe6, 0xe0, 0xb0),
darkslategray=(0x4f, 0x4f, 0x2f),
aquamarine=(0xd4, 0xff, 0x7f),
mediumspringgreen=(0x9a, 0xfa, 0x00),
mediumaquamarine=(0xaa, 0xcd, 0x66),
springgreen=(0x7f, 0xff, 0x00),
mediumseagreen=(0x71, 0xb3, 0x3c),
seagreen=(0x57, 0x8b, 0x2e),
limegreen=(0x32, 0xcd, 0x32),
darkgreen=(0x00, 0x64, 0x00),
green=(0x00, 0x80, 0x00),
lime=(0x00, 0xff, 0x00),
forestgreen=(0x22, 0x8b, 0x22),
darkseagreen=(0x8f, 0xbc, 0x8f),
lightgreen=(0x90, 0xee, 0x90),
palegreen=(0x98, 0xfb, 0x98),
mintcream=(0xfa, 0xff, 0xf5),
honeydew=(0xf0, 0xff, 0xf0),
chartreuse=(0x00, 0xff, 0x7f),
lawngreen=(0x00, 0xfc, 0x7c),
olivedrab=(0x23, 0x8e, 0x6b),
darkolivegreen=(0x2f, 0x6b, 0x55),
yellowgreen=(0x32, 0xcd, 0x9a),
greenyellow=(0x2f, 0xff, 0xad),
beige=(0xdc, 0xf5, 0xf5),
linen=(0xe6, 0xf0, 0xfa),
lightgoldenrodyellow=(0xd2, 0xfa, 0xfa),
olive=(0x00, 0x80, 0x80),
yellow=(0x00, 0xff, 0xff),
lightyellow=(0xe0, 0xff, 0xff),
ivory=(0xf0, 0xff, 0xff),
darkkhaki=(0x6b, 0xb7, 0xbd),
khaki=(0x8c, 0xe6, 0xf0),
palegoldenrod=(0xaa, 0xe8, 0xee),
wheat=(0xb3, 0xde, 0xf5),
gold=(0x00, 0xd7, 0xff),
lemonchiffon=(0xcd, 0xfa, 0xff),
papayawhip=(0xd5, 0xef, 0xff),