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- _base_ = './fovea_r50_fpn_4xb4-1x_coco.py'
- model = dict(
- bbox_head=dict(
- with_deform=True,
- norm_cfg=dict(type='GN', num_groups=32, requires_grad=True)))
- train_pipeline = [
- dict(type='LoadImageFromFile', backend_args={{_base_.backend_args}}),
- dict(type='LoadAnnotations', with_bbox=True),
- dict(
- type='RandomChoiceResize',
- scales=[(1333, 640), (1333, 800)],
- keep_ratio=True),
- dict(type='RandomFlip', prob=0.5),
- dict(type='PackDetInputs')
- ]
- train_dataloader = dict(dataset=dict(pipeline=train_pipeline))
- # learning policy
- max_epochs = 24
- param_scheduler = [
- dict(
- type='LinearLR', start_factor=0.001, by_epoch=False, begin=0, end=500),
- dict(
- type='MultiStepLR',
- begin=0,
- end=max_epochs,
- by_epoch=True,
- milestones=[16, 22],
- gamma=0.1)
- ]
- train_cfg = dict(max_epochs=max_epochs)
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