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- ntu120_xset/b_1/20240728_125719.log +0 -0
- ntu120_xset/b_1/20240728_125719.log.json +0 -0
- ntu120_xset/b_1/b_1.py +98 -0
- ntu120_xset/b_1/best_pred.pkl +3 -0
- ntu120_xset/b_1/best_top1_acc_epoch_149.pth +3 -0
- ntu120_xset/b_2/20240728_125507.log +0 -0
- ntu120_xset/b_2/20240728_125507.log.json +0 -0
- ntu120_xset/b_2/b_2.py +98 -0
- ntu120_xset/b_2/best_pred.pkl +3 -0
- ntu120_xset/b_2/best_top1_acc_epoch_144.pth +3 -0
- ntu120_xset/b_3/20241224_155621.log +0 -0
- ntu120_xset/b_3/20241224_155621.log.json +0 -0
- ntu120_xset/b_3/b_3.py +98 -0
- ntu120_xset/b_3/best_pred.pkl +3 -0
- ntu120_xset/b_3/best_top1_acc_epoch_150.pth +3 -0
- ntu120_xset/bm/20240726_101457.log +0 -0
- ntu120_xset/bm/20240726_101457.log.json +0 -0
- ntu120_xset/bm/best_pred.pkl +3 -0
- ntu120_xset/bm/best_top1_acc_epoch_148.pth +3 -0
- ntu120_xset/bm/bm.py +98 -0
- ntu120_xset/j_1/20240726_101432.log +0 -0
- ntu120_xset/j_1/20240726_101432.log.json +0 -0
- ntu120_xset/j_1/best_pred.pkl +3 -0
- ntu120_xset/j_1/best_top1_acc_epoch_149.pth +3 -0
- ntu120_xset/j_1/j_1.py +96 -0
- ntu120_xset/j_2/20240728_125743.log +0 -0
- ntu120_xset/j_2/20240728_125743.log.json +0 -0
- ntu120_xset/j_2/best_pred.pkl +3 -0
- ntu120_xset/j_2/best_top1_acc_epoch_140.pth +3 -0
- ntu120_xset/j_2/j_2.py +96 -0
- ntu120_xset/j_3/20240728_125731.log +0 -0
- ntu120_xset/j_3/20240728_125731.log.json +0 -0
- ntu120_xset/j_3/best_pred.pkl +3 -0
- ntu120_xset/j_3/best_top1_acc_epoch_144.pth +3 -0
- ntu120_xset/j_3/j_3.py +96 -0
- ntu120_xset/jm/20240726_101511.log +0 -0
- ntu120_xset/jm/20240726_101511.log.json +0 -0
- ntu120_xset/jm/best_pred.pkl +3 -0
- ntu120_xset/jm/best_top1_acc_epoch_144.pth +3 -0
- ntu120_xset/jm/jm.py +96 -0
- ntu120_xset/k_1/20240726_101445.log +0 -0
- ntu120_xset/k_1/20240726_101445.log.json +0 -0
- ntu120_xset/k_1/best_pred.pkl +3 -0
- ntu120_xset/k_1/best_top1_acc_epoch_150.pth +3 -0
- ntu120_xset/k_1/k_1.py +98 -0
- ntu120_xset/k_2/20240728_125812.log +0 -0
- ntu120_xset/k_2/20240728_125812.log.json +0 -0
- ntu120_xset/k_2/best_pred.pkl +3 -0
- ntu120_xset/k_2/best_top1_acc_epoch_149.pth +3 -0
- ntu120_xset/k_2/k_2.py +98 -0
ntu120_xset/b_1/20240728_125719.log
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ntu120_xset/b_1/20240728_125719.log.json
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ntu120_xset/b_1/b_1.py
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@@ -0,0 +1,98 @@
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| 1 |
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modality = 'b'
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| 2 |
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graph = 'nturgb+d'
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work_dir = './work_dirs/test_aclnet/ntu120_xset/b_1'
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| 4 |
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model = dict(
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| 5 |
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type='RecognizerGCN',
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| 6 |
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backbone=dict(
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| 7 |
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type='GCN_Module',
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| 8 |
+
gcn_ratio=0.125,
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| 9 |
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gcn_ctr='T',
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| 10 |
+
gcn_ada='T',
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| 11 |
+
tcn_ms_cfg=[(3, 1), (3, 2), (3, 3), (3, 4), ('max', 3), '1x1'],
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| 12 |
+
graph_cfg=dict(
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| 13 |
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layout='nturgb+d',
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| 14 |
+
mode='random',
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| 15 |
+
num_filter=8,
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| 16 |
+
init_off=0.04,
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| 17 |
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init_std=0.02)),
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| 18 |
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cls_head=dict(type='SimpleHead', data_cfg='ntu120', num_classes=120, in_channels=384))
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| 19 |
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dataset_type = 'PoseDataset'
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| 20 |
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ann_file = '/data/lhd/pyskl_data/nturgbd/ntu120_3danno.pkl'
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| 21 |
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train_pipeline = [
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| 22 |
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dict(type='PreNormalize3D', align_spine=False),
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| 23 |
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dict(type='RandomRot', theta=0.2),
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| 24 |
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dict(type='Spatial_Flip', dataset='nturgb+d', p=0.5),
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| 25 |
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dict(type='GenSkeFeat', feats=['b']),
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| 26 |
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dict(type='UniformSampleDecode', clip_len=100),
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| 27 |
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dict(type='FormatGCNInput'),
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| 28 |
+
dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
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| 29 |
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dict(type='ToTensor', keys=['keypoint'])
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| 30 |
+
]
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| 31 |
+
val_pipeline = [
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| 32 |
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dict(type='PreNormalize3D', align_spine=False),
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| 33 |
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dict(type='GenSkeFeat', feats=['b']),
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| 34 |
+
dict(type='UniformSampleDecode', clip_len=100, num_clips=1),
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| 35 |
+
dict(type='FormatGCNInput'),
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| 36 |
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dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
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| 37 |
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dict(type='ToTensor', keys=['keypoint'])
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| 38 |
+
]
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| 39 |
+
test_pipeline = [
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| 40 |
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dict(type='PreNormalize3D', align_spine=False),
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| 41 |
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dict(type='GenSkeFeat', feats=['b']),
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| 42 |
+
dict(type='UniformSampleDecode', clip_len=100, num_clips=10),
|
| 43 |
+
dict(type='FormatGCNInput'),
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| 44 |
+
dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
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| 45 |
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dict(type='ToTensor', keys=['keypoint'])
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| 46 |
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]
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| 47 |
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data = dict(
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| 48 |
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videos_per_gpu=16,
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| 49 |
+
workers_per_gpu=4,
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| 50 |
+
test_dataloader=dict(videos_per_gpu=1),
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| 51 |
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train=dict(
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| 52 |
+
type='PoseDataset',
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| 53 |
+
ann_file='/data/lhd/pyskl_data/nturgbd/ntu120_3danno.pkl',
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| 54 |
+
pipeline=[
|
| 55 |
+
dict(type='PreNormalize3D', align_spine=False),
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| 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),
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| 60 |
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dict(type='FormatGCNInput'),
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| 61 |
+
dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
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| 62 |
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dict(type='ToTensor', keys=['keypoint'])
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| 63 |
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],
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| 64 |
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split='xset_train'),
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| 65 |
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val=dict(
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| 66 |
+
type='PoseDataset',
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| 67 |
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ann_file='/data/lhd/pyskl_data/nturgbd/ntu120_3danno.pkl',
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| 68 |
+
pipeline=[
|
| 69 |
+
dict(type='PreNormalize3D', align_spine=False),
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| 70 |
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dict(type='GenSkeFeat', feats=['b']),
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| 71 |
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dict(type='UniformSampleDecode', clip_len=100, num_clips=1),
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| 72 |
+
dict(type='FormatGCNInput'),
|
| 73 |
+
dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
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| 74 |
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dict(type='ToTensor', keys=['keypoint'])
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| 75 |
+
],
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| 76 |
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split='xset_val'),
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| 77 |
+
test=dict(
|
| 78 |
+
type='PoseDataset',
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| 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')
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| 98 |
+
gpu_ids = range(0, 1)
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ntu120_xset/b_1/best_pred.pkl
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version https://git-lfs.github.com/spec/v1
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| 2 |
+
oid sha256:c73f9aaf0f2b047d77aca5d8b392518f864881b0091c0979f6669f405f78808e
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| 3 |
+
size 43563860
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ntu120_xset/b_1/best_top1_acc_epoch_149.pth
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@@ -0,0 +1,3 @@
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| 1 |
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version https://git-lfs.github.com/spec/v1
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| 2 |
+
oid sha256:861bde91639e629dab8c5af63ffb64eeb4eea352a7467bdb104ad212d451e069
|
| 3 |
+
size 33129521
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ntu120_xset/b_2/20240728_125507.log
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The diff for this file is too large to render.
See raw diff
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ntu120_xset/b_2/20240728_125507.log.json
ADDED
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The diff for this file is too large to render.
See raw diff
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ntu120_xset/b_2/b_2.py
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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),
|
| 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),
|
| 43 |
+
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)
|
ntu120_xset/b_2/best_pred.pkl
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:34236ab636e1c861c5b96dc496bd1efd0ee89feb4ffa13115af12c0ce5496355
|
| 3 |
+
size 43577025
|
ntu120_xset/b_2/best_top1_acc_epoch_144.pth
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:9f4bb5394151389ea79aabdb4ee9248ea3bfe1f25b32c56daaf63c94e1a36451
|
| 3 |
+
size 33129521
|
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
|
@@ -0,0 +1,98 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 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),
|
| 43 |
+
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)
|
ntu120_xset/b_3/best_pred.pkl
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:14112c3bbeb05d15215eba8d5b1cf9ccefd0b2d4a2a7ac8faaef66c22bb9fbfc
|
| 3 |
+
size 43566143
|
ntu120_xset/b_3/best_top1_acc_epoch_150.pth
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:b49e6f8be736798756c2a146886aa972fa36b2e0816a550cc486555e904e6d33
|
| 3 |
+
size 33129521
|
ntu120_xset/bm/20240726_101457.log
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
ntu120_xset/bm/20240726_101457.log.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
ntu120_xset/bm/best_pred.pkl
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:681b3051b6f0e46930c65b26f2cab9c0e4c902c53e4916b7da45f066d4a5ea6c
|
| 3 |
+
size 43568414
|
ntu120_xset/bm/best_top1_acc_epoch_148.pth
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:eb2a598dae200fd74a0795912b8b390a29fa7bc8e0b1cf2f56b471b20d51f62f
|
| 3 |
+
size 33129521
|
ntu120_xset/bm/bm.py
ADDED
|
@@ -0,0 +1,98 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
modality = 'bm'
|
| 2 |
+
graph = 'nturgb+d'
|
| 3 |
+
work_dir = './work_dirs/test_aclnet/ntu120_xset/bm'
|
| 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=['bm']),
|
| 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=['bm']),
|
| 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=['bm']),
|
| 42 |
+
dict(type='UniformSampleDecode', clip_len=100, num_clips=10),
|
| 43 |
+
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=['bm']),
|
| 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=['bm']),
|
| 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=['bm']),
|
| 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)
|
ntu120_xset/j_1/20240726_101432.log
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
ntu120_xset/j_1/20240726_101432.log.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
ntu120_xset/j_1/best_pred.pkl
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:232013110a40de5d9e320556655771dadddd2d611f38b61d21d4514ae684c2e2
|
| 3 |
+
size 43570123
|
ntu120_xset/j_1/best_top1_acc_epoch_149.pth
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:67361a24ee75ca33bdecd5431c76e033dd8527422d386607aef048027c3b9058
|
| 3 |
+
size 33129521
|
ntu120_xset/j_1/j_1.py
ADDED
|
@@ -0,0 +1,96 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
modality = 'j'
|
| 2 |
+
graph = 'nturgb+d'
|
| 3 |
+
work_dir = './work_dirs/test_aclnet/ntu120_xset/j_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='GenSkeFeat', feats=['j']),
|
| 25 |
+
dict(type='UniformSampleDecode', clip_len=100),
|
| 26 |
+
dict(type='FormatGCNInput'),
|
| 27 |
+
dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
|
| 28 |
+
dict(type='ToTensor', keys=['keypoint'])
|
| 29 |
+
]
|
| 30 |
+
val_pipeline = [
|
| 31 |
+
dict(type='PreNormalize3D', align_spine=False),
|
| 32 |
+
dict(type='GenSkeFeat', feats=['j']),
|
| 33 |
+
dict(type='UniformSampleDecode', clip_len=100, num_clips=1),
|
| 34 |
+
dict(type='FormatGCNInput'),
|
| 35 |
+
dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
|
| 36 |
+
dict(type='ToTensor', keys=['keypoint'])
|
| 37 |
+
]
|
| 38 |
+
test_pipeline = [
|
| 39 |
+
dict(type='PreNormalize3D', align_spine=False),
|
| 40 |
+
dict(type='GenSkeFeat', feats=['j']),
|
| 41 |
+
dict(type='UniformSampleDecode', clip_len=100, num_clips=10),
|
| 42 |
+
dict(type='FormatGCNInput'),
|
| 43 |
+
dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
|
| 44 |
+
dict(type='ToTensor', keys=['keypoint'])
|
| 45 |
+
]
|
| 46 |
+
data = dict(
|
| 47 |
+
videos_per_gpu=16,
|
| 48 |
+
workers_per_gpu=4,
|
| 49 |
+
test_dataloader=dict(videos_per_gpu=1),
|
| 50 |
+
train=dict(
|
| 51 |
+
type='PoseDataset',
|
| 52 |
+
ann_file='/data/lhd/pyskl_data/nturgbd/ntu120_3danno.pkl',
|
| 53 |
+
pipeline=[
|
| 54 |
+
dict(type='PreNormalize3D', align_spine=False),
|
| 55 |
+
dict(type='RandomRot', theta=0.2),
|
| 56 |
+
dict(type='GenSkeFeat', feats=['j']),
|
| 57 |
+
dict(type='UniformSampleDecode', clip_len=100),
|
| 58 |
+
dict(type='FormatGCNInput'),
|
| 59 |
+
dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
|
| 60 |
+
dict(type='ToTensor', keys=['keypoint'])
|
| 61 |
+
],
|
| 62 |
+
split='xset_train'),
|
| 63 |
+
val=dict(
|
| 64 |
+
type='PoseDataset',
|
| 65 |
+
ann_file='/data/lhd/pyskl_data/nturgbd/ntu120_3danno.pkl',
|
| 66 |
+
pipeline=[
|
| 67 |
+
dict(type='PreNormalize3D', align_spine=False),
|
| 68 |
+
dict(type='GenSkeFeat', feats=['j']),
|
| 69 |
+
dict(type='UniformSampleDecode', clip_len=100, num_clips=1),
|
| 70 |
+
dict(type='FormatGCNInput'),
|
| 71 |
+
dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
|
| 72 |
+
dict(type='ToTensor', keys=['keypoint'])
|
| 73 |
+
],
|
| 74 |
+
split='xset_val'),
|
| 75 |
+
test=dict(
|
| 76 |
+
type='PoseDataset',
|
| 77 |
+
ann_file='/data/lhd/pyskl_data/nturgbd/ntu120_3danno.pkl',
|
| 78 |
+
pipeline=[
|
| 79 |
+
dict(type='PreNormalize3D', align_spine=False),
|
| 80 |
+
dict(type='GenSkeFeat', feats=['j']),
|
| 81 |
+
dict(type='UniformSampleDecode', clip_len=100, num_clips=10),
|
| 82 |
+
dict(type='FormatGCNInput'),
|
| 83 |
+
dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
|
| 84 |
+
dict(type='ToTensor', keys=['keypoint'])
|
| 85 |
+
],
|
| 86 |
+
split='xset_val'))
|
| 87 |
+
optimizer = dict(
|
| 88 |
+
type='SGD', lr=0.025, momentum=0.9, weight_decay=0.0005, nesterov=True)
|
| 89 |
+
optimizer_config = dict(grad_clip=None)
|
| 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)
|
ntu120_xset/j_2/20240728_125743.log
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
ntu120_xset/j_2/20240728_125743.log.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
ntu120_xset/j_2/best_pred.pkl
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:29cc61272fbf1067a104fa078b45dfb90342c30db28e1a88ff6289a87b7d6b1d
|
| 3 |
+
size 43565936
|
ntu120_xset/j_2/best_top1_acc_epoch_140.pth
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:9cb645794b965ac758181c9fc232b567479fbee87d1b92ed5dccf137bf273456
|
| 3 |
+
size 33129521
|
ntu120_xset/j_2/j_2.py
ADDED
|
@@ -0,0 +1,96 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
modality = 'j'
|
| 2 |
+
graph = 'nturgb+d'
|
| 3 |
+
work_dir = './work_dirs/test_aclnet/ntu120_xset/j_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='GenSkeFeat', feats=['j']),
|
| 25 |
+
dict(type='UniformSampleDecode', clip_len=100),
|
| 26 |
+
dict(type='FormatGCNInput'),
|
| 27 |
+
dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
|
| 28 |
+
dict(type='ToTensor', keys=['keypoint'])
|
| 29 |
+
]
|
| 30 |
+
val_pipeline = [
|
| 31 |
+
dict(type='PreNormalize3D', align_spine=False),
|
| 32 |
+
dict(type='GenSkeFeat', feats=['j']),
|
| 33 |
+
dict(type='UniformSampleDecode', clip_len=100, num_clips=1),
|
| 34 |
+
dict(type='FormatGCNInput'),
|
| 35 |
+
dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
|
| 36 |
+
dict(type='ToTensor', keys=['keypoint'])
|
| 37 |
+
]
|
| 38 |
+
test_pipeline = [
|
| 39 |
+
dict(type='PreNormalize3D', align_spine=False),
|
| 40 |
+
dict(type='GenSkeFeat', feats=['j']),
|
| 41 |
+
dict(type='UniformSampleDecode', clip_len=100, num_clips=10),
|
| 42 |
+
dict(type='FormatGCNInput'),
|
| 43 |
+
dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
|
| 44 |
+
dict(type='ToTensor', keys=['keypoint'])
|
| 45 |
+
]
|
| 46 |
+
data = dict(
|
| 47 |
+
videos_per_gpu=16,
|
| 48 |
+
workers_per_gpu=4,
|
| 49 |
+
test_dataloader=dict(videos_per_gpu=1),
|
| 50 |
+
train=dict(
|
| 51 |
+
type='PoseDataset',
|
| 52 |
+
ann_file='/data/lhd/pyskl_data/nturgbd/ntu120_3danno.pkl',
|
| 53 |
+
pipeline=[
|
| 54 |
+
dict(type='PreNormalize3D', align_spine=False),
|
| 55 |
+
dict(type='RandomRot', theta=0.2),
|
| 56 |
+
dict(type='GenSkeFeat', feats=['j']),
|
| 57 |
+
dict(type='UniformSampleDecode', clip_len=100),
|
| 58 |
+
dict(type='FormatGCNInput'),
|
| 59 |
+
dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
|
| 60 |
+
dict(type='ToTensor', keys=['keypoint'])
|
| 61 |
+
],
|
| 62 |
+
split='xset_train'),
|
| 63 |
+
val=dict(
|
| 64 |
+
type='PoseDataset',
|
| 65 |
+
ann_file='/data/lhd/pyskl_data/nturgbd/ntu120_3danno.pkl',
|
| 66 |
+
pipeline=[
|
| 67 |
+
dict(type='PreNormalize3D', align_spine=False),
|
| 68 |
+
dict(type='GenSkeFeat', feats=['j']),
|
| 69 |
+
dict(type='UniformSampleDecode', clip_len=100, num_clips=1),
|
| 70 |
+
dict(type='FormatGCNInput'),
|
| 71 |
+
dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
|
| 72 |
+
dict(type='ToTensor', keys=['keypoint'])
|
| 73 |
+
],
|
| 74 |
+
split='xset_val'),
|
| 75 |
+
test=dict(
|
| 76 |
+
type='PoseDataset',
|
| 77 |
+
ann_file='/data/lhd/pyskl_data/nturgbd/ntu120_3danno.pkl',
|
| 78 |
+
pipeline=[
|
| 79 |
+
dict(type='PreNormalize3D', align_spine=False),
|
| 80 |
+
dict(type='GenSkeFeat', feats=['j']),
|
| 81 |
+
dict(type='UniformSampleDecode', clip_len=100, num_clips=10),
|
| 82 |
+
dict(type='FormatGCNInput'),
|
| 83 |
+
dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
|
| 84 |
+
dict(type='ToTensor', keys=['keypoint'])
|
| 85 |
+
],
|
| 86 |
+
split='xset_val'))
|
| 87 |
+
optimizer = dict(
|
| 88 |
+
type='SGD', lr=0.025, momentum=0.9, weight_decay=0.0005, nesterov=True)
|
| 89 |
+
optimizer_config = dict(grad_clip=None)
|
| 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)
|
ntu120_xset/j_3/20240728_125731.log
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
ntu120_xset/j_3/20240728_125731.log.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
ntu120_xset/j_3/best_pred.pkl
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:92abaa16c2f457442326024df3d1b4dadfff510f56711c1898f92f0596640458
|
| 3 |
+
size 43572400
|
ntu120_xset/j_3/best_top1_acc_epoch_144.pth
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:93f7df096d7b2ea8103ec0cb5d7fc8756b079ef199b72c5314bdc412216946cf
|
| 3 |
+
size 33129521
|
ntu120_xset/j_3/j_3.py
ADDED
|
@@ -0,0 +1,96 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
modality = 'j'
|
| 2 |
+
graph = 'nturgb+d'
|
| 3 |
+
work_dir = './work_dirs/test_aclnet/ntu120_xset/j_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='GenSkeFeat', feats=['j']),
|
| 25 |
+
dict(type='UniformSampleDecode', clip_len=100),
|
| 26 |
+
dict(type='FormatGCNInput'),
|
| 27 |
+
dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
|
| 28 |
+
dict(type='ToTensor', keys=['keypoint'])
|
| 29 |
+
]
|
| 30 |
+
val_pipeline = [
|
| 31 |
+
dict(type='PreNormalize3D', align_spine=False),
|
| 32 |
+
dict(type='GenSkeFeat', feats=['j']),
|
| 33 |
+
dict(type='UniformSampleDecode', clip_len=100, num_clips=1),
|
| 34 |
+
dict(type='FormatGCNInput'),
|
| 35 |
+
dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
|
| 36 |
+
dict(type='ToTensor', keys=['keypoint'])
|
| 37 |
+
]
|
| 38 |
+
test_pipeline = [
|
| 39 |
+
dict(type='PreNormalize3D', align_spine=False),
|
| 40 |
+
dict(type='GenSkeFeat', feats=['j']),
|
| 41 |
+
dict(type='UniformSampleDecode', clip_len=100, num_clips=10),
|
| 42 |
+
dict(type='FormatGCNInput'),
|
| 43 |
+
dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
|
| 44 |
+
dict(type='ToTensor', keys=['keypoint'])
|
| 45 |
+
]
|
| 46 |
+
data = dict(
|
| 47 |
+
videos_per_gpu=16,
|
| 48 |
+
workers_per_gpu=4,
|
| 49 |
+
test_dataloader=dict(videos_per_gpu=1),
|
| 50 |
+
train=dict(
|
| 51 |
+
type='PoseDataset',
|
| 52 |
+
ann_file='/data/lhd/pyskl_data/nturgbd/ntu120_3danno.pkl',
|
| 53 |
+
pipeline=[
|
| 54 |
+
dict(type='PreNormalize3D', align_spine=False),
|
| 55 |
+
dict(type='RandomRot', theta=0.2),
|
| 56 |
+
dict(type='GenSkeFeat', feats=['j']),
|
| 57 |
+
dict(type='UniformSampleDecode', clip_len=100),
|
| 58 |
+
dict(type='FormatGCNInput'),
|
| 59 |
+
dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
|
| 60 |
+
dict(type='ToTensor', keys=['keypoint'])
|
| 61 |
+
],
|
| 62 |
+
split='xset_train'),
|
| 63 |
+
val=dict(
|
| 64 |
+
type='PoseDataset',
|
| 65 |
+
ann_file='/data/lhd/pyskl_data/nturgbd/ntu120_3danno.pkl',
|
| 66 |
+
pipeline=[
|
| 67 |
+
dict(type='PreNormalize3D', align_spine=False),
|
| 68 |
+
dict(type='GenSkeFeat', feats=['j']),
|
| 69 |
+
dict(type='UniformSampleDecode', clip_len=100, num_clips=1),
|
| 70 |
+
dict(type='FormatGCNInput'),
|
| 71 |
+
dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
|
| 72 |
+
dict(type='ToTensor', keys=['keypoint'])
|
| 73 |
+
],
|
| 74 |
+
split='xset_val'),
|
| 75 |
+
test=dict(
|
| 76 |
+
type='PoseDataset',
|
| 77 |
+
ann_file='/data/lhd/pyskl_data/nturgbd/ntu120_3danno.pkl',
|
| 78 |
+
pipeline=[
|
| 79 |
+
dict(type='PreNormalize3D', align_spine=False),
|
| 80 |
+
dict(type='GenSkeFeat', feats=['j']),
|
| 81 |
+
dict(type='UniformSampleDecode', clip_len=100, num_clips=10),
|
| 82 |
+
dict(type='FormatGCNInput'),
|
| 83 |
+
dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
|
| 84 |
+
dict(type='ToTensor', keys=['keypoint'])
|
| 85 |
+
],
|
| 86 |
+
split='xset_val'))
|
| 87 |
+
optimizer = dict(
|
| 88 |
+
type='SGD', lr=0.025, momentum=0.9, weight_decay=0.0005, nesterov=True)
|
| 89 |
+
optimizer_config = dict(grad_clip=None)
|
| 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)
|
ntu120_xset/jm/20240726_101511.log
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
ntu120_xset/jm/20240726_101511.log.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
ntu120_xset/jm/best_pred.pkl
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:cac729f45b0aed4e03656fcac301f679aa2b6cb3cb230fe1bb8d8614561655c4
|
| 3 |
+
size 43569248
|
ntu120_xset/jm/best_top1_acc_epoch_144.pth
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:7d238639851f646ea2656a89315f3be0be112a68e40618eed101d0922d9ded0b
|
| 3 |
+
size 33129521
|
ntu120_xset/jm/jm.py
ADDED
|
@@ -0,0 +1,96 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
modality = 'jm'
|
| 2 |
+
graph = 'nturgb+d'
|
| 3 |
+
work_dir = './work_dirs/test_aclnet/ntu120_xset/jm'
|
| 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='GenSkeFeat', feats=['jm']),
|
| 25 |
+
dict(type='UniformSampleDecode', clip_len=100),
|
| 26 |
+
dict(type='FormatGCNInput'),
|
| 27 |
+
dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
|
| 28 |
+
dict(type='ToTensor', keys=['keypoint'])
|
| 29 |
+
]
|
| 30 |
+
val_pipeline = [
|
| 31 |
+
dict(type='PreNormalize3D', align_spine=False),
|
| 32 |
+
dict(type='GenSkeFeat', feats=['jm']),
|
| 33 |
+
dict(type='UniformSampleDecode', clip_len=100, num_clips=1),
|
| 34 |
+
dict(type='FormatGCNInput'),
|
| 35 |
+
dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
|
| 36 |
+
dict(type='ToTensor', keys=['keypoint'])
|
| 37 |
+
]
|
| 38 |
+
test_pipeline = [
|
| 39 |
+
dict(type='PreNormalize3D', align_spine=False),
|
| 40 |
+
dict(type='GenSkeFeat', feats=['jm']),
|
| 41 |
+
dict(type='UniformSampleDecode', clip_len=100, num_clips=10),
|
| 42 |
+
dict(type='FormatGCNInput'),
|
| 43 |
+
dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
|
| 44 |
+
dict(type='ToTensor', keys=['keypoint'])
|
| 45 |
+
]
|
| 46 |
+
data = dict(
|
| 47 |
+
videos_per_gpu=16,
|
| 48 |
+
workers_per_gpu=4,
|
| 49 |
+
test_dataloader=dict(videos_per_gpu=1),
|
| 50 |
+
train=dict(
|
| 51 |
+
type='PoseDataset',
|
| 52 |
+
ann_file='/data/lhd/pyskl_data/nturgbd/ntu120_3danno.pkl',
|
| 53 |
+
pipeline=[
|
| 54 |
+
dict(type='PreNormalize3D', align_spine=False),
|
| 55 |
+
dict(type='RandomRot', theta=0.2),
|
| 56 |
+
dict(type='GenSkeFeat', feats=['jm']),
|
| 57 |
+
dict(type='UniformSampleDecode', clip_len=100),
|
| 58 |
+
dict(type='FormatGCNInput'),
|
| 59 |
+
dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
|
| 60 |
+
dict(type='ToTensor', keys=['keypoint'])
|
| 61 |
+
],
|
| 62 |
+
split='xset_train'),
|
| 63 |
+
val=dict(
|
| 64 |
+
type='PoseDataset',
|
| 65 |
+
ann_file='/data/lhd/pyskl_data/nturgbd/ntu120_3danno.pkl',
|
| 66 |
+
pipeline=[
|
| 67 |
+
dict(type='PreNormalize3D', align_spine=False),
|
| 68 |
+
dict(type='GenSkeFeat', feats=['jm']),
|
| 69 |
+
dict(type='UniformSampleDecode', clip_len=100, num_clips=1),
|
| 70 |
+
dict(type='FormatGCNInput'),
|
| 71 |
+
dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
|
| 72 |
+
dict(type='ToTensor', keys=['keypoint'])
|
| 73 |
+
],
|
| 74 |
+
split='xset_val'),
|
| 75 |
+
test=dict(
|
| 76 |
+
type='PoseDataset',
|
| 77 |
+
ann_file='/data/lhd/pyskl_data/nturgbd/ntu120_3danno.pkl',
|
| 78 |
+
pipeline=[
|
| 79 |
+
dict(type='PreNormalize3D', align_spine=False),
|
| 80 |
+
dict(type='GenSkeFeat', feats=['jm']),
|
| 81 |
+
dict(type='UniformSampleDecode', clip_len=100, num_clips=10),
|
| 82 |
+
dict(type='FormatGCNInput'),
|
| 83 |
+
dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
|
| 84 |
+
dict(type='ToTensor', keys=['keypoint'])
|
| 85 |
+
],
|
| 86 |
+
split='xset_val'))
|
| 87 |
+
optimizer = dict(
|
| 88 |
+
type='SGD', lr=0.025, momentum=0.9, weight_decay=0.0005, nesterov=True)
|
| 89 |
+
optimizer_config = dict(grad_clip=None)
|
| 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)
|
ntu120_xset/k_1/20240726_101445.log
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
ntu120_xset/k_1/20240726_101445.log.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
ntu120_xset/k_1/best_pred.pkl
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
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|
|
|
|
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|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:4f5dacf2d0b1aee9c2fdadf6226d93e62c488de0ebd81ed2445938f5029f6ad3
|
| 3 |
+
size 43566222
|
ntu120_xset/k_1/best_top1_acc_epoch_150.pth
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:4bc01826155b5dff29e095063441dc60f72e8a6bc88c7413059bfe373e873abf
|
| 3 |
+
size 33129521
|
ntu120_xset/k_1/k_1.py
ADDED
|
@@ -0,0 +1,98 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
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|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
|
|
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|
|
|
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|
|
|
|
|
|
|
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|
|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
|
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|
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|
|
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|
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|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
modality = 'k'
|
| 2 |
+
graph = 'nturgb+d'
|
| 3 |
+
work_dir = './work_dirs/test_aclnet/ntu120_xset/k_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=['k']),
|
| 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=['k']),
|
| 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=['k']),
|
| 42 |
+
dict(type='UniformSampleDecode', clip_len=100, num_clips=10),
|
| 43 |
+
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=['k']),
|
| 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=['k']),
|
| 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=['k']),
|
| 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)
|
ntu120_xset/k_2/20240728_125812.log
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
ntu120_xset/k_2/20240728_125812.log.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
ntu120_xset/k_2/best_pred.pkl
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:d92f25c4fd282e91a9cc36cecf37026a22a3d9b9fddbac2658014a79adf83f09
|
| 3 |
+
size 43567278
|
ntu120_xset/k_2/best_top1_acc_epoch_149.pth
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:8da2954c2ade63201de5ef84a22d22bb1ef35f91c7ce823fe98fb6387c57bb2d
|
| 3 |
+
size 33129521
|
ntu120_xset/k_2/k_2.py
ADDED
|
@@ -0,0 +1,98 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
modality = 'k'
|
| 2 |
+
graph = 'nturgb+d'
|
| 3 |
+
work_dir = './work_dirs/test_aclnet/ntu120_xset/k_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=['k']),
|
| 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=['k']),
|
| 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=['k']),
|
| 42 |
+
dict(type='UniformSampleDecode', clip_len=100, num_clips=10),
|
| 43 |
+
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=['k']),
|
| 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=['k']),
|
| 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=['k']),
|
| 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)
|