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  1. ntu120_xset/b_1/20240728_125719.log +0 -0
  2. ntu120_xset/b_1/20240728_125719.log.json +0 -0
  3. ntu120_xset/b_1/b_1.py +98 -0
  4. ntu120_xset/b_1/best_pred.pkl +3 -0
  5. ntu120_xset/b_1/best_top1_acc_epoch_149.pth +3 -0
  6. ntu120_xset/b_2/20240728_125507.log +0 -0
  7. ntu120_xset/b_2/20240728_125507.log.json +0 -0
  8. ntu120_xset/b_2/b_2.py +98 -0
  9. ntu120_xset/b_2/best_pred.pkl +3 -0
  10. ntu120_xset/b_2/best_top1_acc_epoch_144.pth +3 -0
  11. ntu120_xset/b_3/20241224_155621.log +0 -0
  12. ntu120_xset/b_3/20241224_155621.log.json +0 -0
  13. ntu120_xset/b_3/b_3.py +98 -0
  14. ntu120_xset/b_3/best_pred.pkl +3 -0
  15. ntu120_xset/b_3/best_top1_acc_epoch_150.pth +3 -0
  16. ntu120_xset/bm/20240726_101457.log +0 -0
  17. ntu120_xset/bm/20240726_101457.log.json +0 -0
  18. ntu120_xset/bm/best_pred.pkl +3 -0
  19. ntu120_xset/bm/best_top1_acc_epoch_148.pth +3 -0
  20. ntu120_xset/bm/bm.py +98 -0
  21. ntu120_xset/j_1/20240726_101432.log +0 -0
  22. ntu120_xset/j_1/20240726_101432.log.json +0 -0
  23. ntu120_xset/j_1/best_pred.pkl +3 -0
  24. ntu120_xset/j_1/best_top1_acc_epoch_149.pth +3 -0
  25. ntu120_xset/j_1/j_1.py +96 -0
  26. ntu120_xset/j_2/20240728_125743.log +0 -0
  27. ntu120_xset/j_2/20240728_125743.log.json +0 -0
  28. ntu120_xset/j_2/best_pred.pkl +3 -0
  29. ntu120_xset/j_2/best_top1_acc_epoch_140.pth +3 -0
  30. ntu120_xset/j_2/j_2.py +96 -0
  31. ntu120_xset/j_3/20240728_125731.log +0 -0
  32. ntu120_xset/j_3/20240728_125731.log.json +0 -0
  33. ntu120_xset/j_3/best_pred.pkl +3 -0
  34. ntu120_xset/j_3/best_top1_acc_epoch_144.pth +3 -0
  35. ntu120_xset/j_3/j_3.py +96 -0
  36. ntu120_xset/jm/20240726_101511.log +0 -0
  37. ntu120_xset/jm/20240726_101511.log.json +0 -0
  38. ntu120_xset/jm/best_pred.pkl +3 -0
  39. ntu120_xset/jm/best_top1_acc_epoch_144.pth +3 -0
  40. ntu120_xset/jm/jm.py +96 -0
  41. ntu120_xset/k_1/20240726_101445.log +0 -0
  42. ntu120_xset/k_1/20240726_101445.log.json +0 -0
  43. ntu120_xset/k_1/best_pred.pkl +3 -0
  44. ntu120_xset/k_1/best_top1_acc_epoch_150.pth +3 -0
  45. ntu120_xset/k_1/k_1.py +98 -0
  46. ntu120_xset/k_2/20240728_125812.log +0 -0
  47. ntu120_xset/k_2/20240728_125812.log.json +0 -0
  48. ntu120_xset/k_2/best_pred.pkl +3 -0
  49. ntu120_xset/k_2/best_top1_acc_epoch_149.pth +3 -0
  50. ntu120_xset/k_2/k_2.py +98 -0
ntu120_xset/b_1/20240728_125719.log ADDED
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ntu120_xset/b_1/20240728_125719.log.json ADDED
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ntu120_xset/b_1/b_1.py ADDED
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1
+ modality = 'b'
2
+ graph = 'nturgb+d'
3
+ work_dir = './work_dirs/test_aclnet/ntu120_xset/b_1'
4
+ model = dict(
5
+ type='RecognizerGCN',
6
+ backbone=dict(
7
+ type='GCN_Module',
8
+ gcn_ratio=0.125,
9
+ gcn_ctr='T',
10
+ gcn_ada='T',
11
+ tcn_ms_cfg=[(3, 1), (3, 2), (3, 3), (3, 4), ('max', 3), '1x1'],
12
+ graph_cfg=dict(
13
+ layout='nturgb+d',
14
+ mode='random',
15
+ num_filter=8,
16
+ init_off=0.04,
17
+ init_std=0.02)),
18
+ cls_head=dict(type='SimpleHead', data_cfg='ntu120', num_classes=120, in_channels=384))
19
+ dataset_type = 'PoseDataset'
20
+ ann_file = '/data/lhd/pyskl_data/nturgbd/ntu120_3danno.pkl'
21
+ train_pipeline = [
22
+ dict(type='PreNormalize3D', align_spine=False),
23
+ dict(type='RandomRot', theta=0.2),
24
+ dict(type='Spatial_Flip', dataset='nturgb+d', p=0.5),
25
+ dict(type='GenSkeFeat', feats=['b']),
26
+ dict(type='UniformSampleDecode', clip_len=100),
27
+ dict(type='FormatGCNInput'),
28
+ dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
29
+ dict(type='ToTensor', keys=['keypoint'])
30
+ ]
31
+ val_pipeline = [
32
+ dict(type='PreNormalize3D', align_spine=False),
33
+ dict(type='GenSkeFeat', feats=['b']),
34
+ dict(type='UniformSampleDecode', clip_len=100, num_clips=1),
35
+ dict(type='FormatGCNInput'),
36
+ dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
37
+ dict(type='ToTensor', keys=['keypoint'])
38
+ ]
39
+ test_pipeline = [
40
+ dict(type='PreNormalize3D', align_spine=False),
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+ dict(type='GenSkeFeat', feats=['b']),
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+ dict(type='UniformSampleDecode', clip_len=100, num_clips=10),
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+ dict(type='FormatGCNInput'),
44
+ dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
45
+ dict(type='ToTensor', keys=['keypoint'])
46
+ ]
47
+ data = dict(
48
+ videos_per_gpu=16,
49
+ workers_per_gpu=4,
50
+ test_dataloader=dict(videos_per_gpu=1),
51
+ train=dict(
52
+ type='PoseDataset',
53
+ ann_file='/data/lhd/pyskl_data/nturgbd/ntu120_3danno.pkl',
54
+ pipeline=[
55
+ dict(type='PreNormalize3D', align_spine=False),
56
+ dict(type='RandomRot', theta=0.2),
57
+ dict(type='Spatial_Flip', dataset='nturgb+d', p=0.5),
58
+ dict(type='GenSkeFeat', feats=['b']),
59
+ dict(type='UniformSampleDecode', clip_len=100),
60
+ dict(type='FormatGCNInput'),
61
+ dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
62
+ dict(type='ToTensor', keys=['keypoint'])
63
+ ],
64
+ split='xset_train'),
65
+ val=dict(
66
+ type='PoseDataset',
67
+ ann_file='/data/lhd/pyskl_data/nturgbd/ntu120_3danno.pkl',
68
+ pipeline=[
69
+ dict(type='PreNormalize3D', align_spine=False),
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+ dict(type='GenSkeFeat', feats=['b']),
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+ dict(type='UniformSampleDecode', clip_len=100, num_clips=1),
72
+ dict(type='FormatGCNInput'),
73
+ dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
74
+ dict(type='ToTensor', keys=['keypoint'])
75
+ ],
76
+ split='xset_val'),
77
+ test=dict(
78
+ type='PoseDataset',
79
+ ann_file='/data/lhd/pyskl_data/nturgbd/ntu120_3danno.pkl',
80
+ pipeline=[
81
+ dict(type='PreNormalize3D', align_spine=False),
82
+ dict(type='GenSkeFeat', feats=['b']),
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+ dict(type='UniformSampleDecode', clip_len=100, num_clips=10),
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+ dict(type='FormatGCNInput'),
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+ dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
86
+ dict(type='ToTensor', keys=['keypoint'])
87
+ ],
88
+ split='xset_val'))
89
+ optimizer = dict(
90
+ type='SGD', lr=0.025, momentum=0.9, weight_decay=0.0005, nesterov=True)
91
+ optimizer_config = dict(grad_clip=None)
92
+ lr_config = dict(policy='CosineAnnealing', min_lr=0, by_epoch=False)
93
+ total_epochs = 150
94
+ checkpoint_config = dict(interval=1)
95
+ evaluation = dict(interval=1, metrics=['top_k_accuracy'])
96
+ log_config = dict(interval=100, hooks=[dict(type='TextLoggerHook')])
97
+ dist_params = dict(backend='nccl')
98
+ gpu_ids = range(0, 1)
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ntu120_xset/b_2/20240728_125507.log ADDED
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ntu120_xset/b_2/20240728_125507.log.json ADDED
The diff for this file is too large to render. See raw diff
 
ntu120_xset/b_2/b_2.py ADDED
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1
+ modality = 'b'
2
+ graph = 'nturgb+d'
3
+ work_dir = './work_dirs/test_aclnet/ntu120_xset/b_2'
4
+ model = dict(
5
+ type='RecognizerGCN',
6
+ backbone=dict(
7
+ type='GCN_Module',
8
+ gcn_ratio=0.125,
9
+ gcn_ctr='T',
10
+ gcn_ada='T',
11
+ tcn_ms_cfg=[(3, 1), (3, 2), (3, 3), (3, 4), ('max', 3), '1x1'],
12
+ graph_cfg=dict(
13
+ layout='nturgb+d',
14
+ mode='random',
15
+ num_filter=8,
16
+ init_off=0.04,
17
+ init_std=0.02)),
18
+ cls_head=dict(type='SimpleHead', data_cfg='ntu120', num_classes=120, in_channels=384))
19
+ dataset_type = 'PoseDataset'
20
+ ann_file = '/data/lhd/pyskl_data/nturgbd/ntu120_3danno.pkl'
21
+ train_pipeline = [
22
+ dict(type='PreNormalize3D', align_spine=False),
23
+ dict(type='RandomRot', theta=0.2),
24
+ dict(type='Spatial_Flip', dataset='nturgb+d', p=0.5),
25
+ dict(type='GenSkeFeat', feats=['b']),
26
+ dict(type='UniformSampleDecode', clip_len=100),
27
+ dict(type='FormatGCNInput'),
28
+ dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
29
+ dict(type='ToTensor', keys=['keypoint'])
30
+ ]
31
+ val_pipeline = [
32
+ dict(type='PreNormalize3D', align_spine=False),
33
+ dict(type='GenSkeFeat', feats=['b']),
34
+ dict(type='UniformSampleDecode', clip_len=100, num_clips=1),
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+ dict(type='FormatGCNInput'),
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+ dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
37
+ dict(type='ToTensor', keys=['keypoint'])
38
+ ]
39
+ test_pipeline = [
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+ dict(type='PreNormalize3D', align_spine=False),
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+ dict(type='GenSkeFeat', feats=['b']),
42
+ dict(type='UniformSampleDecode', clip_len=100, num_clips=10),
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+ dict(type='FormatGCNInput'),
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+ dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
45
+ dict(type='ToTensor', keys=['keypoint'])
46
+ ]
47
+ data = dict(
48
+ videos_per_gpu=16,
49
+ workers_per_gpu=4,
50
+ test_dataloader=dict(videos_per_gpu=1),
51
+ train=dict(
52
+ type='PoseDataset',
53
+ ann_file='/data/lhd/pyskl_data/nturgbd/ntu120_3danno.pkl',
54
+ pipeline=[
55
+ dict(type='PreNormalize3D', align_spine=False),
56
+ dict(type='RandomRot', theta=0.2),
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+ dict(type='Spatial_Flip', dataset='nturgb+d', p=0.5),
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+ dict(type='GenSkeFeat', feats=['b']),
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+ dict(type='UniformSampleDecode', clip_len=100),
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+ dict(type='FormatGCNInput'),
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+ dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
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+ dict(type='ToTensor', keys=['keypoint'])
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+ ],
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+ split='xset_train'),
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+ val=dict(
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+ type='PoseDataset',
67
+ ann_file='/data/lhd/pyskl_data/nturgbd/ntu120_3danno.pkl',
68
+ pipeline=[
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+ dict(type='PreNormalize3D', align_spine=False),
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+ dict(type='GenSkeFeat', feats=['b']),
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+ dict(type='UniformSampleDecode', clip_len=100, num_clips=1),
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+ dict(type='FormatGCNInput'),
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+ dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
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+ dict(type='ToTensor', keys=['keypoint'])
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+ ],
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+ split='xset_val'),
77
+ test=dict(
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+ type='PoseDataset',
79
+ ann_file='/data/lhd/pyskl_data/nturgbd/ntu120_3danno.pkl',
80
+ pipeline=[
81
+ dict(type='PreNormalize3D', align_spine=False),
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+ dict(type='GenSkeFeat', feats=['b']),
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+ dict(type='UniformSampleDecode', clip_len=100, num_clips=10),
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+ dict(type='FormatGCNInput'),
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+ dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
86
+ dict(type='ToTensor', keys=['keypoint'])
87
+ ],
88
+ split='xset_val'))
89
+ optimizer = dict(
90
+ type='SGD', lr=0.025, momentum=0.9, weight_decay=0.0005, nesterov=True)
91
+ optimizer_config = dict(grad_clip=None)
92
+ lr_config = dict(policy='CosineAnnealing', min_lr=0, by_epoch=False)
93
+ total_epochs = 150
94
+ checkpoint_config = dict(interval=1)
95
+ evaluation = dict(interval=1, metrics=['top_k_accuracy'])
96
+ log_config = dict(interval=100, hooks=[dict(type='TextLoggerHook')])
97
+ dist_params = dict(backend='nccl')
98
+ gpu_ids = range(0, 1)
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ntu120_xset/b_3/20241224_155621.log ADDED
The diff for this file is too large to render. See raw diff
 
ntu120_xset/b_3/20241224_155621.log.json ADDED
The diff for this file is too large to render. See raw diff
 
ntu120_xset/b_3/b_3.py ADDED
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1
+ modality = 'b'
2
+ graph = 'nturgb+d'
3
+ work_dir = './work_dirs/test_aclnet/ntu120_xset/b_3'
4
+ model = dict(
5
+ type='RecognizerGCN',
6
+ backbone=dict(
7
+ type='GCN_Module',
8
+ gcn_ratio=0.125,
9
+ gcn_ctr='T',
10
+ gcn_ada='T',
11
+ tcn_ms_cfg=[(3, 1), (3, 2), (3, 3), (3, 4), ('max', 3), '1x1'],
12
+ graph_cfg=dict(
13
+ layout='nturgb+d',
14
+ mode='random',
15
+ num_filter=8,
16
+ init_off=0.04,
17
+ init_std=0.02)),
18
+ cls_head=dict(type='SimpleHead', data_cfg='ntu120', num_classes=120, in_channels=384))
19
+ dataset_type = 'PoseDataset'
20
+ ann_file = '/data/lhd/pyskl_data/nturgbd/ntu120_3danno.pkl'
21
+ train_pipeline = [
22
+ dict(type='PreNormalize3D', align_spine=False),
23
+ dict(type='RandomRot', theta=0.2),
24
+ dict(type='Spatial_Flip', dataset='nturgb+d', p=0.5),
25
+ dict(type='GenSkeFeat', feats=['b']),
26
+ dict(type='UniformSampleDecode', clip_len=100),
27
+ dict(type='FormatGCNInput'),
28
+ dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
29
+ dict(type='ToTensor', keys=['keypoint'])
30
+ ]
31
+ val_pipeline = [
32
+ dict(type='PreNormalize3D', align_spine=False),
33
+ dict(type='GenSkeFeat', feats=['b']),
34
+ dict(type='UniformSampleDecode', clip_len=100, num_clips=1),
35
+ dict(type='FormatGCNInput'),
36
+ dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
37
+ dict(type='ToTensor', keys=['keypoint'])
38
+ ]
39
+ test_pipeline = [
40
+ dict(type='PreNormalize3D', align_spine=False),
41
+ dict(type='GenSkeFeat', feats=['b']),
42
+ dict(type='UniformSampleDecode', clip_len=100, num_clips=10),
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+ dict(type='FormatGCNInput'),
44
+ dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
45
+ dict(type='ToTensor', keys=['keypoint'])
46
+ ]
47
+ data = dict(
48
+ videos_per_gpu=16,
49
+ workers_per_gpu=4,
50
+ test_dataloader=dict(videos_per_gpu=1),
51
+ train=dict(
52
+ type='PoseDataset',
53
+ ann_file='/data/lhd/pyskl_data/nturgbd/ntu120_3danno.pkl',
54
+ pipeline=[
55
+ dict(type='PreNormalize3D', align_spine=False),
56
+ dict(type='RandomRot', theta=0.2),
57
+ dict(type='Spatial_Flip', dataset='nturgb+d', p=0.5),
58
+ dict(type='GenSkeFeat', feats=['b']),
59
+ dict(type='UniformSampleDecode', clip_len=100),
60
+ dict(type='FormatGCNInput'),
61
+ dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
62
+ dict(type='ToTensor', keys=['keypoint'])
63
+ ],
64
+ split='xset_train'),
65
+ val=dict(
66
+ type='PoseDataset',
67
+ ann_file='/data/lhd/pyskl_data/nturgbd/ntu120_3danno.pkl',
68
+ pipeline=[
69
+ dict(type='PreNormalize3D', align_spine=False),
70
+ dict(type='GenSkeFeat', feats=['b']),
71
+ dict(type='UniformSampleDecode', clip_len=100, num_clips=1),
72
+ dict(type='FormatGCNInput'),
73
+ dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
74
+ dict(type='ToTensor', keys=['keypoint'])
75
+ ],
76
+ split='xset_val'),
77
+ test=dict(
78
+ type='PoseDataset',
79
+ ann_file='/data/lhd/pyskl_data/nturgbd/ntu120_3danno.pkl',
80
+ pipeline=[
81
+ dict(type='PreNormalize3D', align_spine=False),
82
+ dict(type='GenSkeFeat', feats=['b']),
83
+ dict(type='UniformSampleDecode', clip_len=100, num_clips=10),
84
+ dict(type='FormatGCNInput'),
85
+ dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
86
+ dict(type='ToTensor', keys=['keypoint'])
87
+ ],
88
+ split='xset_val'))
89
+ optimizer = dict(
90
+ type='SGD', lr=0.025, momentum=0.9, weight_decay=0.0005, nesterov=True)
91
+ optimizer_config = dict(grad_clip=None)
92
+ lr_config = dict(policy='CosineAnnealing', min_lr=0, by_epoch=False)
93
+ total_epochs = 150
94
+ checkpoint_config = dict(interval=1)
95
+ evaluation = dict(interval=1, metrics=['top_k_accuracy'])
96
+ log_config = dict(interval=100, hooks=[dict(type='TextLoggerHook')])
97
+ dist_params = dict(backend='nccl')
98
+ gpu_ids = range(0, 1)
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+ log_config = dict(interval=100, hooks=[dict(type='TextLoggerHook')])
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+ dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
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+ ]
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+ type='PoseDataset',
52
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54
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89
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90
+ lr_config = dict(policy='CosineAnnealing', min_lr=0, by_epoch=False)
91
+ total_epochs = 150
92
+ checkpoint_config = dict(interval=1)
93
+ evaluation = dict(interval=1, metrics=['top_k_accuracy'])
94
+ log_config = dict(interval=100, hooks=[dict(type='TextLoggerHook')])
95
+ dist_params = dict(backend='nccl')
96
+ gpu_ids = range(0, 1)
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+ ann_file = '/data/lhd/pyskl_data/nturgbd/ntu120_3danno.pkl'
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+ dict(type='RandomRot', theta=0.2),
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+ dict(type='GenSkeFeat', feats=['jm']),
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+ dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
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+ dict(type='ToTensor', keys=['keypoint'])
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+ checkpoint_config = dict(interval=1)
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+ log_config = dict(interval=100, hooks=[dict(type='TextLoggerHook')])
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+ cls_head=dict(type='SimpleHead', data_cfg='ntu120', num_classes=120, in_channels=384))
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20
+ ann_file = '/data/lhd/pyskl_data/nturgbd/ntu120_3danno.pkl'
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+ dict(type='Spatial_Flip', dataset='nturgb+d', p=0.5),
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51
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91
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92
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93
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94
+ checkpoint_config = dict(interval=1)
95
+ evaluation = dict(interval=1, metrics=['top_k_accuracy'])
96
+ log_config = dict(interval=100, hooks=[dict(type='TextLoggerHook')])
97
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98
+ gpu_ids = range(0, 1)
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1
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+ graph = 'nturgb+d'
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+ work_dir = './work_dirs/test_aclnet/ntu120_xset/k_2'
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5
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+ cls_head=dict(type='SimpleHead', data_cfg='ntu120', num_classes=120, in_channels=384))
19
+ dataset_type = 'PoseDataset'
20
+ ann_file = '/data/lhd/pyskl_data/nturgbd/ntu120_3danno.pkl'
21
+ train_pipeline = [
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23
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50
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51
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52
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53
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54
+ pipeline=[
55
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56
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79
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80
+ pipeline=[
81
+ dict(type='PreNormalize3D', align_spine=False),
82
+ dict(type='GenSkeFeat', feats=['k']),
83
+ dict(type='UniformSampleDecode', clip_len=100, num_clips=10),
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+ dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
86
+ dict(type='ToTensor', keys=['keypoint'])
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+ ],
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+ split='xset_val'))
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91
+ optimizer_config = dict(grad_clip=None)
92
+ lr_config = dict(policy='CosineAnnealing', min_lr=0, by_epoch=False)
93
+ total_epochs = 150
94
+ checkpoint_config = dict(interval=1)
95
+ evaluation = dict(interval=1, metrics=['top_k_accuracy'])
96
+ log_config = dict(interval=100, hooks=[dict(type='TextLoggerHook')])
97
+ dist_params = dict(backend='nccl')
98
+ gpu_ids = range(0, 1)