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_base_ = [
'dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015.py',
]
load_from = None
_base_.model.backbone = dict(
type='mmdet.ResNet',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=-1,
norm_cfg=dict(type='BN', requires_grad=True),
norm_eval=True,
style='pytorch',
init_cfg=dict(type='Pretrained', checkpoint='torchvision://resnet50'))
_base_.train_dataloader.num_workers = 24
_base_.optim_wrapper.optimizer.lr = 0.003
param_scheduler = [
dict(type='LinearLR', end=200, start_factor=0.001),
dict(type='PolyLR', power=0.9, eta_min=1e-7, begin=200, end=1200),
]
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