| _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)))) | |