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model = dict(
type="TemporalMaxer",
projection=dict(
type="TemporalMaxerProj",
in_channels=2048,
out_channels=512,
arch=(2, 0, 5), # feature projection layers, downsampling layer
conv_cfg=dict(kernel_size=3),
norm_cfg=dict(type="LN"),
),
neck=dict(
type="FPNIdentity",
in_channels=512,
out_channels=512,
num_levels=6,
),
rpn_head=dict(
type="TemporalMaxerHead",
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,
loss=dict(
cls_loss=dict(type="FocalLoss"),
reg_loss=dict(type="DIOULoss"),
),
assigner=dict(
type="AnchorFreeSimOTAAssigner",
iou_weight=2,
cls_weight=1.0,
center_radius=1.5,
keep_percent=1.0,
confuse_weight=0.0,
),
),
)
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