OpenMMLab Detection Toolbox and Benchmark
https://mmdetection.readthedocs.io/
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48 lines
1.5 KiB
48 lines
1.5 KiB
_base_ = '../retinanet/retinanet_r50_fpn_1x_coco.py' |
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# model settings |
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model = dict( |
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type='FSAF', |
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bbox_head=dict( |
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type='FSAFHead', |
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num_classes=80, |
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in_channels=256, |
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stacked_convs=4, |
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feat_channels=256, |
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reg_decoded_bbox=True, |
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# Only anchor-free branch is implemented. The anchor generator only |
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# generates 1 anchor at each feature point, as a substitute of the |
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# grid of features. |
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anchor_generator=dict( |
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type='AnchorGenerator', |
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octave_base_scale=1, |
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scales_per_octave=1, |
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ratios=[1.0], |
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strides=[8, 16, 32, 64, 128]), |
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bbox_coder=dict(_delete_=True, type='TBLRBBoxCoder', normalizer=4.0), |
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loss_cls=dict( |
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type='FocalLoss', |
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use_sigmoid=True, |
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gamma=2.0, |
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alpha=0.25, |
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loss_weight=1.0, |
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reduction='none'), |
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loss_bbox=dict( |
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_delete_=True, |
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type='IoULoss', |
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eps=1e-6, |
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loss_weight=1.0, |
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reduction='none')), |
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# training and testing settings |
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train_cfg=dict( |
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assigner=dict( |
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_delete_=True, |
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type='CenterRegionAssigner', |
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pos_scale=0.2, |
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neg_scale=0.2, |
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min_pos_iof=0.01), |
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allowed_border=-1, |
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pos_weight=-1, |
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debug=False)) |
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optimizer = dict(type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0001) |
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optimizer_config = dict( |
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_delete_=True, grad_clip=dict(max_norm=10, norm_type=2))
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