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- _base_ = './rtmdet-ins_l_8xb32-300e_coco.py'
- model = dict(
- backbone=dict(deepen_factor=1.33, widen_factor=1.25),
- neck=dict(
- in_channels=[320, 640, 1280], out_channels=320, num_csp_blocks=4),
- bbox_head=dict(in_channels=320, feat_channels=320))
- base_lr = 0.002
- # optimizer
- optim_wrapper = dict(optimizer=dict(lr=base_lr))
- # learning rate
- param_scheduler = [
- dict(
- type='LinearLR',
- start_factor=1.0e-5,
- by_epoch=False,
- begin=0,
- end=1000),
- dict(
- # use cosine lr from 150 to 300 epoch
- type='CosineAnnealingLR',
- eta_min=base_lr * 0.05,
- begin=_base_.max_epochs // 2,
- end=_base_.max_epochs,
- T_max=_base_.max_epochs // 2,
- by_epoch=True,
- convert_to_iter_based=True),
- ]
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