OpenMMLab Detection Toolbox and Benchmark
https://mmdetection.readthedocs.io/
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50 lines
1.6 KiB
50 lines
1.6 KiB
_base_ = [ |
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'../_base_/models/retinanet_r50_fpn.py', |
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'../_base_/datasets/coco_detection.py', |
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'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py' |
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] |
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# model settings |
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model = dict( |
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bbox_head=dict( |
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_delete_=True, |
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type='SABLRetinaHead', |
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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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approx_anchor_generator=dict( |
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type='AnchorGenerator', |
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octave_base_scale=4, |
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scales_per_octave=3, |
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ratios=[0.5, 1.0, 2.0], |
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strides=[8, 16, 32, 64, 128]), |
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square_anchor_generator=dict( |
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type='AnchorGenerator', |
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ratios=[1.0], |
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scales=[4], |
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strides=[8, 16, 32, 64, 128]), |
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bbox_coder=dict( |
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type='BucketingBBoxCoder', num_buckets=14, scale_factor=3.0), |
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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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loss_bbox_cls=dict( |
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type='CrossEntropyLoss', use_sigmoid=True, loss_weight=1.5), |
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loss_bbox_reg=dict( |
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type='SmoothL1Loss', beta=1.0 / 9.0, loss_weight=1.5)), |
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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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type='ApproxMaxIoUAssigner', |
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pos_iou_thr=0.5, |
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neg_iou_thr=0.4, |
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min_pos_iou=0.0, |
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ignore_iof_thr=-1), |
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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 |
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optimizer = dict(type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0001)
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