| _base_ = '../retinanet/retinanet_r50_fpn_1x_coco.py' | |
| # model settings | |
| model = dict( | |
| type='FSAF', | |
| bbox_head=dict( | |
| type='FSAFHead', | |
| num_classes=80, | |
| in_channels=256, | |
| stacked_convs=4, | |
| feat_channels=256, | |
| reg_decoded_bbox=True, | |
| # Only anchor-free branch is implemented. The anchor generator only | |
| # generates 1 anchor at each feature point, as a substitute of the | |
| # grid of features. | |
| anchor_generator=dict( | |
| type='AnchorGenerator', | |
| octave_base_scale=1, | |
| scales_per_octave=1, | |
| ratios=[1.0], | |
| strides=[8, 16, 32, 64, 128]), | |
| bbox_coder=dict(_delete_=True, type='TBLRBBoxCoder', normalizer=4.0), | |
| loss_cls=dict( | |
| type='FocalLoss', | |
| use_sigmoid=True, | |
| gamma=2.0, | |
| alpha=0.25, | |
| loss_weight=1.0, | |
| reduction='none'), | |
| loss_bbox=dict( | |
| _delete_=True, | |
| type='IoULoss', | |
| eps=1e-6, | |
| loss_weight=1.0, | |
| reduction='none')), | |
| # training and testing settings | |
| train_cfg=dict( | |
| assigner=dict( | |
| _delete_=True, | |
| type='CenterRegionAssigner', | |
| pos_scale=0.2, | |
| neg_scale=0.2, | |
| min_pos_iof=0.01), | |
| allowed_border=-1, | |
| pos_weight=-1, | |
| debug=False)) | |
| optim_wrapper = dict(clip_grad=dict(max_norm=10, norm_type=2)) | |