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_base_ = [ |
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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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|
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model = dict( |
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type='FCOS', |
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data_preprocessor=dict( |
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type='DetDataPreprocessor', |
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mean=[102.9801, 115.9465, 122.7717], |
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std=[1.0, 1.0, 1.0], |
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bgr_to_rgb=False, |
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pad_size_divisor=32), |
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backbone=dict( |
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type='ResNet', |
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depth=50, |
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num_stages=4, |
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out_indices=(0, 1, 2, 3), |
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frozen_stages=1, |
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norm_cfg=dict(type='BN', requires_grad=False), |
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norm_eval=True, |
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style='caffe', |
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init_cfg=dict( |
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type='Pretrained', |
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checkpoint='open-mmlab://detectron/resnet50_caffe')), |
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neck=dict( |
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type='FPN', |
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in_channels=[256, 512, 1024, 2048], |
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out_channels=256, |
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start_level=1, |
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add_extra_convs='on_output', |
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num_outs=5, |
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relu_before_extra_convs=True), |
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bbox_head=dict( |
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type='FCOSHead', |
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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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strides=[8, 16, 32, 64, 128], |
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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=dict(type='IoULoss', loss_weight=1.0), |
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loss_centerness=dict( |
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type='CrossEntropyLoss', use_sigmoid=True, loss_weight=1.0)), |
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|
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test_cfg=dict( |
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nms_pre=1000, |
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min_bbox_size=0, |
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score_thr=0.05, |
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nms=dict(type='nms', iou_threshold=0.5), |
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max_per_img=100)) |
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|
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param_scheduler = [ |
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dict(type='ConstantLR', factor=1.0 / 3, by_epoch=False, begin=0, end=500), |
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dict( |
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type='MultiStepLR', |
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begin=0, |
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end=12, |
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by_epoch=True, |
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milestones=[8, 11], |
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gamma=0.1) |
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] |
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|
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optim_wrapper = dict( |
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optimizer=dict(lr=0.01), |
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paramwise_cfg=dict(bias_lr_mult=2., bias_decay_mult=0.), |
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clip_grad=dict(max_norm=35, norm_type=2)) |
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|
