Newer
Older
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
backbone=dict(
type='ResNeXt',
depth=101,
groups=64,
base_width=4,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=True),
norm_eval=True,
style='pytorch',
dcn=dict(type='DCN', deform_groups=1, fallback_on_stride=False),
stage_with_dcn=(False, True, True, True)),
neck=dict(
type='FPN',
in_channels=[256, 512, 1024, 2048],
out_channels=256,
num_outs=5),
rpn_head=dict(
type='RPNHead',
in_channels=256,
feat_channels=256,
anchor_generator=dict(
type='AnchorGenerator',
scales=[8],
ratios=[0.5, 1.0, 2.0],
strides=[4, 8, 16, 32, 64]),
bbox_coder=dict(
type='DeltaXYWHBBoxCoder',
target_means=[0.0, 0.0, 0.0, 0.0],
target_stds=[1.0, 1.0, 1.0, 1.0]),
loss_cls=dict(
type='CrossEntropyLoss', use_sigmoid=True, loss_weight=1.0),
loss_bbox=dict(
type='SmoothL1Loss', beta=0.1111111111111111, loss_weight=1.0)),
roi_head=dict(
type='HybridTaskCascadeRoIHead',
interleaved=True,
mask_info_flow=True,
num_stages=3,
stage_loss_weights=[1, 0.5, 0.25],
bbox_roi_extractor=dict(
type='SingleRoIExtractor',
roi_layer=dict(type='RoIAlign', output_size=7, sampling_ratio=0),
out_channels=256,
featmap_strides=[4, 8, 16, 32]),
bbox_head=[
dict(
type='Shared2FCBBoxHead',
in_channels=256,
fc_out_channels=1024,
roi_feat_size=7,
num_classes=273,
bbox_coder=dict(
type='DeltaXYWHBBoxCoder',
target_means=[0.0, 0.0, 0.0, 0.0],
target_stds=[0.1, 0.1, 0.2, 0.2]),
reg_class_agnostic=True,
loss_cls=dict(
type='LabelSmoothCrossEntropyLoss',
use_sigmoid=False,
loss_weight=1.0,
label_smooth=0.1),
loss_bbox=dict(type='SmoothL1Loss', beta=1.0,
loss_weight=1.0)),
dict(
type='Shared2FCBBoxHead',
in_channels=256,
fc_out_channels=1024,
roi_feat_size=7,
num_classes=273,
bbox_coder=dict(
type='DeltaXYWHBBoxCoder',
target_means=[0.0, 0.0, 0.0, 0.0],
target_stds=[0.05, 0.05, 0.1, 0.1]),
reg_class_agnostic=True,
loss_cls=dict(
type='LabelSmoothCrossEntropyLoss',
use_sigmoid=False,
loss_weight=1.0,
label_smooth=0.1),
loss_bbox=dict(type='SmoothL1Loss', beta=1.0,
loss_weight=1.0)),
dict(
type='Shared2FCBBoxHead',
in_channels=256,
fc_out_channels=1024,
roi_feat_size=7,
num_classes=273,
bbox_coder=dict(
type='DeltaXYWHBBoxCoder',
target_means=[0.0, 0.0, 0.0, 0.0],
target_stds=[0.033, 0.033, 0.067, 0.067]),
reg_class_agnostic=True,
loss_cls=dict(
type='LabelSmoothCrossEntropyLoss',
use_sigmoid=False,
loss_weight=1.0,
label_smooth=0.1),
loss_bbox=dict(type='SmoothL1Loss', beta=1.0, loss_weight=1.0))
],
mask_roi_extractor=dict(
type='SingleRoIExtractor',
roi_layer=dict(type='RoIAlign', output_size=14, sampling_ratio=0),
out_channels=256,
featmap_strides=[4, 8, 16, 32]),
mask_head=[
dict(
type='HTCMaskHead',
with_conv_res=False,
num_convs=4,
in_channels=256,
conv_out_channels=256,
num_classes=273,
loss_mask=dict(
type='CrossEntropyLoss', use_mask=True, loss_weight=1.0)),
dict(
type='HTCMaskHead',
num_convs=4,
in_channels=256,
conv_out_channels=256,
num_classes=273,
loss_mask=dict(
type='CrossEntropyLoss', use_mask=True, loss_weight=1.0)),
dict(
type='HTCMaskHead',
num_convs=4,
in_channels=256,
conv_out_channels=256,
num_classes=273,
loss_mask=dict(
type='CrossEntropyLoss', use_mask=True, loss_weight=1.0))
]))
train_cfg = dict(
rpn=dict(
assigner=dict(
type='MaxIoUAssigner',
pos_iou_thr=0.7,
neg_iou_thr=0.3,
min_pos_iou=0.3,
ignore_iof_thr=-1),
sampler=dict(
type='RandomSampler',
num=256,
pos_fraction=0.5,
neg_pos_ub=-1,
add_gt_as_proposals=False),
allowed_border=0,
pos_weight=-1,
debug=False),
rpn_proposal=dict(
nms_across_levels=False,
nms_pre=2500,
nms_post=2000,
max_num=2000,
nms_thr=0.7,
min_bbox_size=0),
rcnn=[
dict(
assigner=dict(
type='MaxIoUAssigner',
pos_iou_thr=0.5,
neg_iou_thr=0.5,
min_pos_iou=0.5,
ignore_iof_thr=-1),
sampler=dict(
type='RandomSampler',
num=512,
pos_fraction=0.25,
neg_pos_ub=-1,
add_gt_as_proposals=True),
mask_size=28,
pos_weight=-1,
debug=False),
dict(
assigner=dict(
type='MaxIoUAssigner',
pos_iou_thr=0.6,
neg_iou_thr=0.6,
min_pos_iou=0.6,
ignore_iof_thr=-1),
sampler=dict(
type='RandomSampler',
num=512,
pos_fraction=0.25,
neg_pos_ub=-1,
add_gt_as_proposals=True),
mask_size=28,
pos_weight=-1,
debug=False),
dict(
assigner=dict(
type='MaxIoUAssigner',
pos_iou_thr=0.7,
neg_iou_thr=0.7,
min_pos_iou=0.7,
ignore_iof_thr=-1),
sampler=dict(
type='RandomSampler',
num=512,
pos_fraction=0.25,
neg_pos_ub=-1,
add_gt_as_proposals=True),
mask_size=28,
pos_weight=-1,
debug=False)
])
test_cfg = dict(
rpn=dict(
nms_across_levels=False,
nms_pre=2500,
nms_post=2000,
max_num=1500,
nms_thr=0.8,
min_bbox_size=0),
rcnn=dict(
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
nms=dict(type='nms', iou_thr=0.35),
max_per_img=100,
mask_thr_binary=0.4))
classes = [
'water', 'pear', 'egg', 'grapes', 'butter', 'bread-white', 'jam',
'bread-whole-wheat', 'apple', 'tea-green', 'white-coffee-with-caffeine',
'tea-black', 'mixed-salad-chopped-without-sauce', 'cheese', 'tomato-sauce',
'pasta-spaghetti', 'carrot', 'onion', 'beef-cut-into-stripes-only-meat',
'rice-noodles-vermicelli', 'salad-leaf-salad-green', 'bread-grain',
'espresso-with-caffeine', 'banana', 'mixed-vegetables', 'bread-wholemeal',
'savoury-puff-pastry', 'wine-white', 'dried-meat', 'fresh-cheese',
'red-radish', 'hard-cheese', 'ham-raw', 'bread-fruit',
'oil-vinegar-salad-dressing', 'tomato', 'cauliflower', 'potato-gnocchi',
'wine-red', 'sauce-cream', 'pasta-linguini-parpadelle-tagliatelle',
'french-beans', 'almonds', 'dark-chocolate', 'mandarine',
'semi-hard-cheese', 'croissant', 'sushi', 'berries', 'biscuits',
'thickened-cream-35', 'corn', 'celeriac', 'alfa-sprouts', 'chickpeas',
'leaf-spinach', 'rice', 'chocolate-cookies', 'pineapple', 'tart',
'coffee-with-caffeine', 'focaccia', 'pizza-with-vegetables-baked',
'soup-vegetable', 'bread-toast', 'potatoes-steamed', 'spaetzle',
'frying-sausage', 'lasagne-meat-prepared', 'boisson-au-glucose-50g',
'ma1-4esli', 'peanut-butter', 'chips-french-fries', 'mushroom',
'ratatouille', 'veggie-burger', 'country-fries',
'yaourt-yahourt-yogourt-ou-yoghourt-natural', 'hummus', 'fish', 'beer',
'peanut', 'pizza-margherita-baked', 'pickle', 'ham-cooked',
'cake-chocolate', 'bread-french-white-flour', 'sauce-mushroom',
'rice-basmati', 'soup-of-lentils-dahl-dhal', 'pumpkin', 'witloof-chicory',
'vegetable-au-gratin-baked', 'balsamic-salad-dressing', 'pasta-penne',
'tea-peppermint', 'soup-pumpkin',
'quiche-with-cheese-baked-with-puff-pastry', 'mango',
'green-bean-steamed-without-addition-of-salt', 'cucumber',
'bread-half-white', 'pasta', 'beef-filet', 'pasta-twist',
'pasta-wholemeal', 'walnut', 'soft-cheese', 'salmon-smoked',
'sweet-pepper', 'sauce-soya', 'chicken-breast', 'rice-whole-grain',
'bread-nut', 'green-olives',
'roll-of-half-white-or-white-flour-with-large-void', 'parmesan',
'cappuccino', 'flakes-oat', 'mayonnaise', 'chicken', 'cheese-for-raclette',
'orange', 'goat-cheese-soft', 'tuna', 'tomme', 'apple-pie', 'rosti',
'broccoli', 'beans-kidney', 'white-cabbage', 'ketchup',
'salt-cake-vegetables-filled', 'pistachio', 'feta', 'salmon', 'avocado',
'sauce-pesto', 'salad-rocket', 'pizza-with-ham-baked', 'gruya-re',
'ristretto-with-caffeine', 'risotto-without-cheese-cooked',
'crunch-ma1-4esli', 'braided-white-loaf', 'peas',
'chicken-curry-cream-coconut-milk-curry-spices-paste', 'bolognaise-sauce',
'bacon-frying', 'salami', 'lentils', 'mushrooms',
'mashed-potatoes-prepared-with-full-fat-milk-with-butter', 'fennel',
'chocolate-mousse', 'corn-crisps', 'sweet-potato',
'bircherma1-4esli-prepared-no-sugar-added',
'beetroot-steamed-without-addition-of-salt', 'sauce-savoury', 'leek',
'milk', 'tea', 'fruit-salad', 'bread-rye', 'salad-lambs-ear',
'potatoes-au-gratin-dauphinois-prepared', 'red-cabbage', 'praline',
'bread-black', 'black-olives', 'mozzarella', 'bacon-cooking',
'pomegranate', 'hamburger-bread-meat-ketchup', 'curry-vegetarian', 'honey',
'juice-orange', 'cookies', 'mixed-nuts', 'breadcrumbs-unspiced',
'chicken-leg', 'raspberries', 'beef-sirloin-steak', 'salad-dressing',
'shrimp-prawn-large', 'sour-cream', 'greek-salad', 'sauce-roast',
'zucchini', 'greek-yaourt-yahourt-yogourt-ou-yoghourt', 'cashew-nut',
'meat-terrine-pata-c', 'chicken-cut-into-stripes-only-meat', 'couscous',
'bread-wholemeal-toast', 'craape-plain', 'bread-5-grain', 'tofu',
'water-mineral', 'ham-croissant', 'juice-apple', 'falafel-balls',
'egg-scrambled-prepared', 'brioche', 'bread-pita', 'pasta-haprnli',
'blue-mould-cheese', 'vegetable-mix-peas-and-carrots', 'quinoa', 'crisps',
'beef', 'butter-spread-puree-almond', 'beef-minced-only-meat',
'hazelnut-chocolate-spread-nutella-ovomaltine-caotina', 'chocolate',
'nectarine', 'ice-tea', 'applesauce-unsweetened-canned',
'syrup-diluted-ready-to-drink', 'sugar-melon', 'bread-sourdough',
'rusk-wholemeal', 'gluten-free-bread', 'shrimp-prawn-small',
'french-salad-dressing', 'pancakes', 'milk-chocolate', 'pork',
'dairy-ice-cream', 'guacamole', 'sausage', 'herbal-tea', 'fruit-coulis',
'water-with-lemon-juice', 'brownie', 'lemon', 'veal-sausage', 'dates',
'roll-with-pieces-of-chocolate', 'taboula-c-prepared-with-couscous',
'croissant-with-chocolate-filling', 'eggplant', 'sesame-seeds',
'cottage-cheese', 'fruit-tart', 'cream-cheese', 'tea-verveine', 'tiramisu',
'grits-polenta-maize-flour', 'pasta-noodles', 'artichoke', 'blueberries',
'mixed-seeds', 'caprese-salad-tomato-mozzarella', 'omelette-plain',
'hazelnut', 'kiwi', 'dried-raisins', 'kolhrabi', 'plums', 'beetroot-raw',
'cream', 'fajita-bread-only', 'apricots', 'kefir-drink', 'bread',
'strawberries', 'wine-rosa-c', 'watermelon-fresh', 'green-asparagus',
'white-asparagus', 'peach'
]
dataset_type = 'CocoDataset'
data_root = 'data/'
img_norm_cfg = dict(
mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
albu_train_transforms = [
dict(
type='ShiftScaleRotate',
shift_limit=0.0625,
scale_limit=0.0,
rotate_limit=30,
interpolation=2,
p=0.3),
dict(type='RandomRotate90', p=0.5),
dict(
type='RandomBrightnessContrast',
brightness_limit=[0.1, 0.3],
contrast_limit=[0.1, 0.3],
p=0.3),
dict(
type='OneOf',
transforms=[
dict(type='Blur'),
dict(type='MotionBlur'),
dict(type='GaussNoise'),
dict(type='ImageCompression', quality_lower=75)
],
p=0.4),
dict(
type='CoarseDropout',
max_holes=30,
max_height=30,
max_width=30,
min_holes=5,
min_height=10,
min_width=10,
fill_value=[103.53, 116.28, 123.675],
p=0.4)
]
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations', with_bbox=True, with_mask=True),
dict(
type='Resize',
img_scale=[(1600, 400), (1600, 1400)],
multiscale_mode='range',
keep_ratio=True),
dict(
type='Albu',
transforms=[
dict(
type='ShiftScaleRotate',
shift_limit=0.0625,
scale_limit=0.0,
rotate_limit=30,
interpolation=2,
p=0.3),
dict(type='RandomRotate90', p=0.5),
dict(
type='RandomBrightnessContrast',
brightness_limit=[0.1, 0.3],
contrast_limit=[0.1, 0.3],
p=0.3),
dict(
type='OneOf',
transforms=[
dict(type='Blur'),
dict(type='MotionBlur'),
dict(type='GaussNoise'),
dict(type='ImageCompression', quality_lower=75)
],
p=0.4),
dict(
type='CoarseDropout',
max_holes=30,
max_height=30,
max_width=30,
min_holes=5,
min_height=10,
min_width=10,
fill_value=[103.53, 116.28, 123.675],
p=0.4)
],
bbox_params=dict(
type='BboxParams',
format='pascal_voc',
label_fields=['gt_labels'],
min_visibility=0.0,
filter_lost_elements=True),
keymap=dict(img='image', gt_masks='masks', gt_bboxes='bboxes'),
update_pad_shape=False,
skip_img_without_anno=False),
dict(type='RandomFlip', flip_ratio=0.5),
dict(
type='Normalize',
mean=[123.675, 116.28, 103.53],
std=[58.395, 57.12, 57.375],
to_rgb=True),
dict(type='Pad', size_divisor=32),
dict(type='DefaultFormatBundle'),
dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels', 'gt_masks'])
]
test_pipeline = [
dict(type='LoadImageFromFile'),
dict(
type='MultiScaleFlipAug',
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
transforms=[
dict(type='Resize', keep_ratio=True),
dict(type='RandomFlip'),
dict(
type='Normalize',
mean=[123.675, 116.28, 103.53],
std=[58.395, 57.12, 57.375],
to_rgb=True),
dict(type='Pad', size_divisor=32),
dict(type='ImageToTensor', keys=['img']),
dict(type='Collect', keys=['img'])
])
]
data = dict(
samples_per_gpu=2,
workers_per_gpu=0,
train=dict(
type='CocoDataset',
ann_file='data/combined_anns.json',
img_prefix='data/train/images/',
pipeline=[
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations', with_bbox=True, with_mask=True),
dict(
type='Resize',
img_scale=[(1600, 400), (1600, 1400)],
multiscale_mode='range',
keep_ratio=True),
dict(
type='Albu',
transforms=[
dict(
type='ShiftScaleRotate',
shift_limit=0.0625,
scale_limit=0.0,
rotate_limit=30,
interpolation=2,
p=0.3),
dict(type='RandomRotate90', p=0.5),
dict(
type='RandomBrightnessContrast',
brightness_limit=[0.1, 0.3],
contrast_limit=[0.1, 0.3],
p=0.3),
dict(
type='OneOf',
transforms=[
dict(type='Blur'),
dict(type='MotionBlur'),
dict(type='GaussNoise'),
dict(type='ImageCompression', quality_lower=75)
],
p=0.4),
dict(
type='CoarseDropout',
max_holes=30,
max_height=30,
max_width=30,
min_holes=5,
min_height=10,
min_width=10,
fill_value=[103.53, 116.28, 123.675],
p=0.4)
],
bbox_params=dict(
type='BboxParams',
format='pascal_voc',
label_fields=['gt_labels'],
min_visibility=0.0,
filter_lost_elements=True),
keymap=dict(img='image', gt_masks='masks', gt_bboxes='bboxes'),
update_pad_shape=False,
skip_img_without_anno=False),
dict(type='RandomFlip', flip_ratio=0.5),
dict(
type='Normalize',
mean=[123.675, 116.28, 103.53],
std=[58.395, 57.12, 57.375],
to_rgb=True),
dict(type='Pad', size_divisor=32),
dict(type='DefaultFormatBundle'),
dict(
type='Collect',
keys=['img', 'gt_bboxes', 'gt_labels', 'gt_masks'])
],
classes=[
'water', 'pear', 'egg', 'grapes', 'butter', 'bread-white', 'jam',
'bread-whole-wheat', 'apple', 'tea-green',
'white-coffee-with-caffeine', 'tea-black',
'mixed-salad-chopped-without-sauce', 'cheese', 'tomato-sauce',
'pasta-spaghetti', 'carrot', 'onion',
'beef-cut-into-stripes-only-meat', 'rice-noodles-vermicelli',
'salad-leaf-salad-green', 'bread-grain', 'espresso-with-caffeine',
'banana', 'mixed-vegetables', 'bread-wholemeal',
'savoury-puff-pastry', 'wine-white', 'dried-meat', 'fresh-cheese',
'red-radish', 'hard-cheese', 'ham-raw', 'bread-fruit',
'oil-vinegar-salad-dressing', 'tomato', 'cauliflower',
'potato-gnocchi', 'wine-red', 'sauce-cream',
'pasta-linguini-parpadelle-tagliatelle', 'french-beans', 'almonds',
'dark-chocolate', 'mandarine', 'semi-hard-cheese', 'croissant',
'sushi', 'berries', 'biscuits', 'thickened-cream-35', 'corn',
'celeriac', 'alfa-sprouts', 'chickpeas', 'leaf-spinach', 'rice',
'chocolate-cookies', 'pineapple', 'tart', 'coffee-with-caffeine',
'focaccia', 'pizza-with-vegetables-baked', 'soup-vegetable',
'bread-toast', 'potatoes-steamed', 'spaetzle', 'frying-sausage',
'lasagne-meat-prepared', 'boisson-au-glucose-50g', 'ma1-4esli',
'peanut-butter', 'chips-french-fries', 'mushroom', 'ratatouille',
'veggie-burger', 'country-fries',
'yaourt-yahourt-yogourt-ou-yoghourt-natural', 'hummus', 'fish',
'beer', 'peanut', 'pizza-margherita-baked', 'pickle', 'ham-cooked',
'cake-chocolate', 'bread-french-white-flour', 'sauce-mushroom',
'rice-basmati', 'soup-of-lentils-dahl-dhal', 'pumpkin',
'witloof-chicory', 'vegetable-au-gratin-baked',
'balsamic-salad-dressing', 'pasta-penne', 'tea-peppermint',
'soup-pumpkin', 'quiche-with-cheese-baked-with-puff-pastry',
'mango', 'green-bean-steamed-without-addition-of-salt', 'cucumber',
'bread-half-white', 'pasta', 'beef-filet', 'pasta-twist',
'pasta-wholemeal', 'walnut', 'soft-cheese', 'salmon-smoked',
'sweet-pepper', 'sauce-soya', 'chicken-breast', 'rice-whole-grain',
'bread-nut', 'green-olives',
'roll-of-half-white-or-white-flour-with-large-void', 'parmesan',
'cappuccino', 'flakes-oat', 'mayonnaise', 'chicken',
'cheese-for-raclette', 'orange', 'goat-cheese-soft', 'tuna',
'tomme', 'apple-pie', 'rosti', 'broccoli', 'beans-kidney',
'white-cabbage', 'ketchup', 'salt-cake-vegetables-filled',
'pistachio', 'feta', 'salmon', 'avocado', 'sauce-pesto',
'salad-rocket', 'pizza-with-ham-baked', 'gruya-re',
'ristretto-with-caffeine', 'risotto-without-cheese-cooked',
'crunch-ma1-4esli', 'braided-white-loaf', 'peas',
'chicken-curry-cream-coconut-milk-curry-spices-paste',
'bolognaise-sauce', 'bacon-frying', 'salami', 'lentils',
'mushrooms',
'mashed-potatoes-prepared-with-full-fat-milk-with-butter',
'fennel', 'chocolate-mousse', 'corn-crisps', 'sweet-potato',
'bircherma1-4esli-prepared-no-sugar-added',
'beetroot-steamed-without-addition-of-salt', 'sauce-savoury',
'leek', 'milk', 'tea', 'fruit-salad', 'bread-rye',
'salad-lambs-ear', 'potatoes-au-gratin-dauphinois-prepared',
'red-cabbage', 'praline', 'bread-black', 'black-olives',
'mozzarella', 'bacon-cooking', 'pomegranate',
'hamburger-bread-meat-ketchup', 'curry-vegetarian', 'honey',
'juice-orange', 'cookies', 'mixed-nuts', 'breadcrumbs-unspiced',
'chicken-leg', 'raspberries', 'beef-sirloin-steak',
'salad-dressing', 'shrimp-prawn-large', 'sour-cream',
'greek-salad', 'sauce-roast', 'zucchini',
'greek-yaourt-yahourt-yogourt-ou-yoghourt', 'cashew-nut',
'meat-terrine-pata-c', 'chicken-cut-into-stripes-only-meat',
'couscous', 'bread-wholemeal-toast', 'craape-plain',
'bread-5-grain', 'tofu', 'water-mineral', 'ham-croissant',
'juice-apple', 'falafel-balls', 'egg-scrambled-prepared',
'brioche', 'bread-pita', 'pasta-haprnli', 'blue-mould-cheese',
'vegetable-mix-peas-and-carrots', 'quinoa', 'crisps', 'beef',
'butter-spread-puree-almond', 'beef-minced-only-meat',
'hazelnut-chocolate-spread-nutella-ovomaltine-caotina',
'chocolate', 'nectarine', 'ice-tea',
'applesauce-unsweetened-canned', 'syrup-diluted-ready-to-drink',
'sugar-melon', 'bread-sourdough', 'rusk-wholemeal',
'gluten-free-bread', 'shrimp-prawn-small', 'french-salad-dressing',
'pancakes', 'milk-chocolate', 'pork', 'dairy-ice-cream',
'guacamole', 'sausage', 'herbal-tea', 'fruit-coulis',
'water-with-lemon-juice', 'brownie', 'lemon', 'veal-sausage',
'dates', 'roll-with-pieces-of-chocolate',
'taboula-c-prepared-with-couscous',
'croissant-with-chocolate-filling', 'eggplant', 'sesame-seeds',
'cottage-cheese', 'fruit-tart', 'cream-cheese', 'tea-verveine',
'tiramisu', 'grits-polenta-maize-flour', 'pasta-noodles',
'artichoke', 'blueberries', 'mixed-seeds',
'caprese-salad-tomato-mozzarella', 'omelette-plain', 'hazelnut',
'kiwi', 'dried-raisins', 'kolhrabi', 'plums', 'beetroot-raw',
'cream', 'fajita-bread-only', 'apricots', 'kefir-drink', 'bread',
'strawberries', 'wine-rosa-c', 'watermelon-fresh',
'green-asparagus', 'white-asparagus', 'peach'
]),
val=dict(
type='CocoDataset',
ann_file='data/val/edited_val_r3.json',
img_prefix='data/val/images/',
pipeline=[
dict(type='LoadImageFromFile'),
dict(
type='MultiScaleFlipAug',
img_scale=[(850, 850)],
flip=True,
transforms=[
dict(type='Resize', keep_ratio=True),
dict(type='RandomFlip'),
dict(
type='Normalize',
mean=[123.675, 116.28, 103.53],
std=[58.395, 57.12, 57.375],
to_rgb=True),
dict(type='Pad', size_divisor=32),
dict(type='ImageToTensor', keys=['img']),
dict(type='Collect', keys=['img'])
])
],
classes=[
'water', 'pear', 'egg', 'grapes', 'butter', 'bread-white', 'jam',
'bread-whole-wheat', 'apple', 'tea-green',
'white-coffee-with-caffeine', 'tea-black',
'mixed-salad-chopped-without-sauce', 'cheese', 'tomato-sauce',
'pasta-spaghetti', 'carrot', 'onion',
'beef-cut-into-stripes-only-meat', 'rice-noodles-vermicelli',
'salad-leaf-salad-green', 'bread-grain', 'espresso-with-caffeine',
'banana', 'mixed-vegetables', 'bread-wholemeal',
'savoury-puff-pastry', 'wine-white', 'dried-meat', 'fresh-cheese',
'red-radish', 'hard-cheese', 'ham-raw', 'bread-fruit',
'oil-vinegar-salad-dressing', 'tomato', 'cauliflower',
'potato-gnocchi', 'wine-red', 'sauce-cream',
'pasta-linguini-parpadelle-tagliatelle', 'french-beans', 'almonds',
'dark-chocolate', 'mandarine', 'semi-hard-cheese', 'croissant',
'sushi', 'berries', 'biscuits', 'thickened-cream-35', 'corn',
'celeriac', 'alfa-sprouts', 'chickpeas', 'leaf-spinach', 'rice',
'chocolate-cookies', 'pineapple', 'tart', 'coffee-with-caffeine',
'focaccia', 'pizza-with-vegetables-baked', 'soup-vegetable',
'bread-toast', 'potatoes-steamed', 'spaetzle', 'frying-sausage',
'lasagne-meat-prepared', 'boisson-au-glucose-50g', 'ma1-4esli',
'peanut-butter', 'chips-french-fries', 'mushroom', 'ratatouille',
'veggie-burger', 'country-fries',
'yaourt-yahourt-yogourt-ou-yoghourt-natural', 'hummus', 'fish',
'beer', 'peanut', 'pizza-margherita-baked', 'pickle', 'ham-cooked',
'cake-chocolate', 'bread-french-white-flour', 'sauce-mushroom',
'rice-basmati', 'soup-of-lentils-dahl-dhal', 'pumpkin',
'witloof-chicory', 'vegetable-au-gratin-baked',
'balsamic-salad-dressing', 'pasta-penne', 'tea-peppermint',
'soup-pumpkin', 'quiche-with-cheese-baked-with-puff-pastry',
'mango', 'green-bean-steamed-without-addition-of-salt', 'cucumber',
'bread-half-white', 'pasta', 'beef-filet', 'pasta-twist',
'pasta-wholemeal', 'walnut', 'soft-cheese', 'salmon-smoked',
'sweet-pepper', 'sauce-soya', 'chicken-breast', 'rice-whole-grain',
'bread-nut', 'green-olives',
'roll-of-half-white-or-white-flour-with-large-void', 'parmesan',
'cappuccino', 'flakes-oat', 'mayonnaise', 'chicken',
'cheese-for-raclette', 'orange', 'goat-cheese-soft', 'tuna',
'tomme', 'apple-pie', 'rosti', 'broccoli', 'beans-kidney',
'white-cabbage', 'ketchup', 'salt-cake-vegetables-filled',
'pistachio', 'feta', 'salmon', 'avocado', 'sauce-pesto',
'salad-rocket', 'pizza-with-ham-baked', 'gruya-re',
'ristretto-with-caffeine', 'risotto-without-cheese-cooked',
'crunch-ma1-4esli', 'braided-white-loaf', 'peas',
'chicken-curry-cream-coconut-milk-curry-spices-paste',
'bolognaise-sauce', 'bacon-frying', 'salami', 'lentils',
'mushrooms',
'mashed-potatoes-prepared-with-full-fat-milk-with-butter',
'fennel', 'chocolate-mousse', 'corn-crisps', 'sweet-potato',
'bircherma1-4esli-prepared-no-sugar-added',
'beetroot-steamed-without-addition-of-salt', 'sauce-savoury',
'leek', 'milk', 'tea', 'fruit-salad', 'bread-rye',
'salad-lambs-ear', 'potatoes-au-gratin-dauphinois-prepared',
'red-cabbage', 'praline', 'bread-black', 'black-olives',
'mozzarella', 'bacon-cooking', 'pomegranate',
'hamburger-bread-meat-ketchup', 'curry-vegetarian', 'honey',
'juice-orange', 'cookies', 'mixed-nuts', 'breadcrumbs-unspiced',
'chicken-leg', 'raspberries', 'beef-sirloin-steak',
'salad-dressing', 'shrimp-prawn-large', 'sour-cream',
'greek-salad', 'sauce-roast', 'zucchini',
'greek-yaourt-yahourt-yogourt-ou-yoghourt', 'cashew-nut',
'meat-terrine-pata-c', 'chicken-cut-into-stripes-only-meat',
'couscous', 'bread-wholemeal-toast', 'craape-plain',
'bread-5-grain', 'tofu', 'water-mineral', 'ham-croissant',
'juice-apple', 'falafel-balls', 'egg-scrambled-prepared',
'brioche', 'bread-pita', 'pasta-haprnli', 'blue-mould-cheese',
'vegetable-mix-peas-and-carrots', 'quinoa', 'crisps', 'beef',
'butter-spread-puree-almond', 'beef-minced-only-meat',
'hazelnut-chocolate-spread-nutella-ovomaltine-caotina',
'chocolate', 'nectarine', 'ice-tea',
'applesauce-unsweetened-canned', 'syrup-diluted-ready-to-drink',
'sugar-melon', 'bread-sourdough', 'rusk-wholemeal',
'gluten-free-bread', 'shrimp-prawn-small', 'french-salad-dressing',
'pancakes', 'milk-chocolate', 'pork', 'dairy-ice-cream',
'guacamole', 'sausage', 'herbal-tea', 'fruit-coulis',
'water-with-lemon-juice', 'brownie', 'lemon', 'veal-sausage',
'dates', 'roll-with-pieces-of-chocolate',
'taboula-c-prepared-with-couscous',
'croissant-with-chocolate-filling', 'eggplant', 'sesame-seeds',
'cottage-cheese', 'fruit-tart', 'cream-cheese', 'tea-verveine',
'tiramisu', 'grits-polenta-maize-flour', 'pasta-noodles',
'artichoke', 'blueberries', 'mixed-seeds',
'caprese-salad-tomato-mozzarella', 'omelette-plain', 'hazelnut',
'kiwi', 'dried-raisins', 'kolhrabi', 'plums', 'beetroot-raw',
'cream', 'fajita-bread-only', 'apricots', 'kefir-drink', 'bread',
'strawberries', 'wine-rosa-c', 'watermelon-fresh',
'green-asparagus', 'white-asparagus', 'peach'
]),
test=dict(
type='CocoDataset',
ann_file='data/test.json',
img_prefix=None,
pipeline=[
dict(type='LoadImageFromFile'),
dict(
type='MultiScaleFlipAug',
img_scale=[(850, 850)],
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
transforms=[
dict(type='Resize', keep_ratio=True),
dict(type='RandomFlip'),
dict(
type='Normalize',
mean=[123.675, 116.28, 103.53],
std=[58.395, 57.12, 57.375],
to_rgb=True),
dict(type='Pad', size_divisor=32),
dict(type='ImageToTensor', keys=['img']),
dict(type='Collect', keys=['img'])
])
],
classes=[
'water', 'pear', 'egg', 'grapes', 'butter', 'bread-white', 'jam',
'bread-whole-wheat', 'apple', 'tea-green',
'white-coffee-with-caffeine', 'tea-black',
'mixed-salad-chopped-without-sauce', 'cheese', 'tomato-sauce',
'pasta-spaghetti', 'carrot', 'onion',
'beef-cut-into-stripes-only-meat', 'rice-noodles-vermicelli',
'salad-leaf-salad-green', 'bread-grain', 'espresso-with-caffeine',
'banana', 'mixed-vegetables', 'bread-wholemeal',
'savoury-puff-pastry', 'wine-white', 'dried-meat', 'fresh-cheese',
'red-radish', 'hard-cheese', 'ham-raw', 'bread-fruit',
'oil-vinegar-salad-dressing', 'tomato', 'cauliflower',
'potato-gnocchi', 'wine-red', 'sauce-cream',
'pasta-linguini-parpadelle-tagliatelle', 'french-beans', 'almonds',
'dark-chocolate', 'mandarine', 'semi-hard-cheese', 'croissant',
'sushi', 'berries', 'biscuits', 'thickened-cream-35', 'corn',
'celeriac', 'alfa-sprouts', 'chickpeas', 'leaf-spinach', 'rice',
'chocolate-cookies', 'pineapple', 'tart', 'coffee-with-caffeine',
'focaccia', 'pizza-with-vegetables-baked', 'soup-vegetable',
'bread-toast', 'potatoes-steamed', 'spaetzle', 'frying-sausage',
'lasagne-meat-prepared', 'boisson-au-glucose-50g', 'ma1-4esli',
'peanut-butter', 'chips-french-fries', 'mushroom', 'ratatouille',
'veggie-burger', 'country-fries',
'yaourt-yahourt-yogourt-ou-yoghourt-natural', 'hummus', 'fish',
'beer', 'peanut', 'pizza-margherita-baked', 'pickle', 'ham-cooked',
'cake-chocolate', 'bread-french-white-flour', 'sauce-mushroom',
'rice-basmati', 'soup-of-lentils-dahl-dhal', 'pumpkin',
'witloof-chicory', 'vegetable-au-gratin-baked',
'balsamic-salad-dressing', 'pasta-penne', 'tea-peppermint',
'soup-pumpkin', 'quiche-with-cheese-baked-with-puff-pastry',
'mango', 'green-bean-steamed-without-addition-of-salt', 'cucumber',
'bread-half-white', 'pasta', 'beef-filet', 'pasta-twist',
'pasta-wholemeal', 'walnut', 'soft-cheese', 'salmon-smoked',
'sweet-pepper', 'sauce-soya', 'chicken-breast', 'rice-whole-grain',
'bread-nut', 'green-olives',
'roll-of-half-white-or-white-flour-with-large-void', 'parmesan',
'cappuccino', 'flakes-oat', 'mayonnaise', 'chicken',
'cheese-for-raclette', 'orange', 'goat-cheese-soft', 'tuna',
'tomme', 'apple-pie', 'rosti', 'broccoli', 'beans-kidney',
'white-cabbage', 'ketchup', 'salt-cake-vegetables-filled',
'pistachio', 'feta', 'salmon', 'avocado', 'sauce-pesto',
'salad-rocket', 'pizza-with-ham-baked', 'gruya-re',
'ristretto-with-caffeine', 'risotto-without-cheese-cooked',
'crunch-ma1-4esli', 'braided-white-loaf', 'peas',
'chicken-curry-cream-coconut-milk-curry-spices-paste',
'bolognaise-sauce', 'bacon-frying', 'salami', 'lentils',
'mushrooms',
'mashed-potatoes-prepared-with-full-fat-milk-with-butter',
'fennel', 'chocolate-mousse', 'corn-crisps', 'sweet-potato',
'bircherma1-4esli-prepared-no-sugar-added',
'beetroot-steamed-without-addition-of-salt', 'sauce-savoury',
'leek', 'milk', 'tea', 'fruit-salad', 'bread-rye',
'salad-lambs-ear', 'potatoes-au-gratin-dauphinois-prepared',
'red-cabbage', 'praline', 'bread-black', 'black-olives',
'mozzarella', 'bacon-cooking', 'pomegranate',
'hamburger-bread-meat-ketchup', 'curry-vegetarian', 'honey',
'juice-orange', 'cookies', 'mixed-nuts', 'breadcrumbs-unspiced',
'chicken-leg', 'raspberries', 'beef-sirloin-steak',
'salad-dressing', 'shrimp-prawn-large', 'sour-cream',
'greek-salad', 'sauce-roast', 'zucchini',
'greek-yaourt-yahourt-yogourt-ou-yoghourt', 'cashew-nut',
'meat-terrine-pata-c', 'chicken-cut-into-stripes-only-meat',
'couscous', 'bread-wholemeal-toast', 'craape-plain',
'bread-5-grain', 'tofu', 'water-mineral', 'ham-croissant',
'juice-apple', 'falafel-balls', 'egg-scrambled-prepared',
'brioche', 'bread-pita', 'pasta-haprnli', 'blue-mould-cheese',
'vegetable-mix-peas-and-carrots', 'quinoa', 'crisps', 'beef',
'butter-spread-puree-almond', 'beef-minced-only-meat',
'hazelnut-chocolate-spread-nutella-ovomaltine-caotina',
'chocolate', 'nectarine', 'ice-tea',
'applesauce-unsweetened-canned', 'syrup-diluted-ready-to-drink',
'sugar-melon', 'bread-sourdough', 'rusk-wholemeal',
'gluten-free-bread', 'shrimp-prawn-small', 'french-salad-dressing',
'pancakes', 'milk-chocolate', 'pork', 'dairy-ice-cream',
'guacamole', 'sausage', 'herbal-tea', 'fruit-coulis',
'water-with-lemon-juice', 'brownie', 'lemon', 'veal-sausage',
'dates', 'roll-with-pieces-of-chocolate',
'taboula-c-prepared-with-couscous',
'croissant-with-chocolate-filling', 'eggplant', 'sesame-seeds',
'cottage-cheese', 'fruit-tart', 'cream-cheese', 'tea-verveine',
'tiramisu', 'grits-polenta-maize-flour', 'pasta-noodles',
'artichoke', 'blueberries', 'mixed-seeds',
'caprese-salad-tomato-mozzarella', 'omelette-plain', 'hazelnut',
'kiwi', 'dried-raisins', 'kolhrabi', 'plums', 'beetroot-raw',
'cream', 'fajita-bread-only', 'apricots', 'kefir-drink', 'bread',
'strawberries', 'wine-rosa-c', 'watermelon-fresh',
'green-asparagus', 'white-asparagus', 'peach'
]))
evaluation = dict(metric=['bbox', 'segm'])
optimizer = dict(type='SGD', lr=0.0025, momentum=0.9, weight_decay=0.0001)
optimizer_config = dict(grad_clip=None)
lr_config = dict(
policy='step',
warmup='linear',
warmup_iters=500,
warmup_ratio=0.001,
step=[18, 22])
total_epochs = 24
checkpoint_config = dict(interval=1, create_symlink=False)
log_config = dict(
interval=50,
hooks=[dict(type='TensorboardLoggerHook'),
dict(type='TextLoggerHook')])
dist_params = dict(backend='nccl')
log_level = 'INFO'
work_dir = './work_dirs/htc_label_smooth_all'
load_from = './old_models/epoch_14.pth'
resume_from = './work_dirs/htc_label_smooth_all/epoch_11.pth'
workflow = [('train', 1)]
gpu_ids = range(0, 1)