mirror of https://github.com/alibaba/EasyCV.git
51 lines
1.4 KiB
Python
51 lines
1.4 KiB
Python
# model settings
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model = dict(
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type='Detection',
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pretrained=True,
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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=(1, 2, 3, 4),
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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='pytorch'),
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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', # use P5
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num_outs=5,
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relu_before_extra_convs=True),
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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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center_sampling=True,
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center_sample_radius=1.5,
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norm_on_bbox=True,
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centerness_on_reg=True,
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conv_cfg=None,
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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='GIoULoss', 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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norm_cfg=dict(type='GN', num_groups=32, requires_grad=True),
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conv_bias=True,
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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=0.6),
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max_per_img=100)))
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