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- _base_ = 'mask-rcnn_r50_fpn_crop640-50e_coco.py'
- norm_cfg = dict(type='BN', requires_grad=True)
- model = dict(
- neck=dict(
- type='FPG',
- in_channels=[256, 512, 1024, 2048],
- out_channels=256,
- inter_channels=256,
- num_outs=5,
- stack_times=9,
- paths=['bu'] * 9,
- same_down_trans=None,
- same_up_trans=dict(
- type='conv',
- kernel_size=3,
- stride=2,
- padding=1,
- norm_cfg=norm_cfg,
- inplace=False,
- order=('act', 'conv', 'norm')),
- across_lateral_trans=dict(
- type='conv',
- kernel_size=1,
- norm_cfg=norm_cfg,
- inplace=False,
- order=('act', 'conv', 'norm')),
- across_down_trans=dict(
- type='interpolation_conv',
- mode='nearest',
- kernel_size=3,
- norm_cfg=norm_cfg,
- order=('act', 'conv', 'norm'),
- inplace=False),
- across_up_trans=None,
- across_skip_trans=dict(
- type='conv',
- kernel_size=1,
- norm_cfg=norm_cfg,
- inplace=False,
- order=('act', 'conv', 'norm')),
- output_trans=dict(
- type='last_conv',
- kernel_size=3,
- order=('act', 'conv', 'norm'),
- inplace=False),
- norm_cfg=norm_cfg,
- skip_inds=[(0, 1, 2, 3), (0, 1, 2), (0, 1), (0, ), ()]))
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