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- _base_ = '../mask_rcnn/mask-rcnn_r50_fpn_1x_coco.py'
- # model settings
- model = dict(
- roi_head=dict(
- bbox_roi_extractor=dict(
- type='GenericRoIExtractor',
- aggregation='sum',
- roi_layer=dict(type='RoIAlign', output_size=7, sampling_ratio=2),
- out_channels=256,
- featmap_strides=[4, 8, 16, 32],
- pre_cfg=dict(
- type='ConvModule',
- in_channels=256,
- out_channels=256,
- kernel_size=5,
- padding=2,
- inplace=False,
- ),
- post_cfg=dict(
- type='GeneralizedAttention',
- in_channels=256,
- spatial_range=-1,
- num_heads=6,
- attention_type='0100',
- kv_stride=2)),
- mask_roi_extractor=dict(
- type='GenericRoIExtractor',
- roi_layer=dict(type='RoIAlign', output_size=14, sampling_ratio=2),
- out_channels=256,
- featmap_strides=[4, 8, 16, 32],
- pre_cfg=dict(
- type='ConvModule',
- in_channels=256,
- out_channels=256,
- kernel_size=5,
- padding=2,
- inplace=False,
- ),
- post_cfg=dict(
- type='GeneralizedAttention',
- in_channels=256,
- spatial_range=-1,
- num_heads=6,
- attention_type='0100',
- kv_stride=2))))
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