|
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model = dict( |
|
|
type="ActionFormer", |
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|
projection=dict( |
|
|
type="Conv1DTransformerProj", |
|
|
in_channels=2048, |
|
|
out_channels=512, |
|
|
arch=(2, 2, 5), |
|
|
conv_cfg=dict(kernel_size=3, proj_pdrop=0.0), |
|
|
norm_cfg=dict(type="LN"), |
|
|
attn_cfg=dict(n_head=4, n_mha_win_size=19), |
|
|
path_pdrop=0.1, |
|
|
use_abs_pe=False, |
|
|
max_seq_len=2304, |
|
|
), |
|
|
neck=dict( |
|
|
type="FPNIdentity", |
|
|
in_channels=512, |
|
|
out_channels=512, |
|
|
num_levels=6, |
|
|
), |
|
|
rpn_head=dict( |
|
|
type="ActionFormerHead", |
|
|
num_classes=20, |
|
|
in_channels=512, |
|
|
feat_channels=512, |
|
|
num_convs=2, |
|
|
cls_prior_prob=0.01, |
|
|
prior_generator=dict( |
|
|
type="PointGenerator", |
|
|
strides=[1, 2, 4, 8, 16, 32], |
|
|
regression_range=[(0, 4), (4, 8), (8, 16), (16, 32), (32, 64), (64, 10000)], |
|
|
), |
|
|
loss_normalizer=100, |
|
|
loss_normalizer_momentum=0.9, |
|
|
center_sample="radius", |
|
|
center_sample_radius=1.5, |
|
|
label_smoothing=0.0, |
|
|
loss=dict( |
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|
cls_loss=dict(type="FocalLoss"), |
|
|
reg_loss=dict(type="DIOULoss"), |
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|
), |
|
|
), |
|
|
) |
|
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|
