| model = dict( | |
| type='DBNet', | |
| 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=False, | |
| style='pytorch', | |
| dcn=dict(type='DCNv2', deform_groups=1, fallback_on_stride=False), | |
| init_cfg=dict(type='Pretrained', checkpoint='torchvision://resnet50'), | |
| stage_with_dcn=(False, True, True, True)), | |
| neck=dict( | |
| type='FPNC', | |
| in_channels=[256, 512, 1024, 2048], | |
| lateral_channels=256, | |
| asf_cfg=dict(attention_type='ScaleChannelSpatial')), | |
| bbox_head=dict( | |
| type='DBHead', | |
| in_channels=256, | |
| loss=dict(type='DBLoss', alpha=5.0, beta=10.0, bbce_loss=True), | |
| postprocessor=dict( | |
| type='DBPostprocessor', text_repr_type='quad', | |
| epsilon_ratio=0.002)), | |
| train_cfg=None, | |
| test_cfg=None) | |