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44 lines
1.1 KiB
Python
44 lines
1.1 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=(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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head=dict(
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type='DETRHead',
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transformer=dict(
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type='DetrTransformer',
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in_channels=2048,
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num_queries=100,
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d_model=256,
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nhead=8,
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num_encoder_layers=6,
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num_decoder_layers=6,
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dim_feedforward=2048,
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dropout=0.1,
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activation='relu',
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normalize_before=False,
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return_intermediate_dec=True,
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),
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num_classes=80,
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in_channels=2048,
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embed_dims=256,
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eos_coef=0.1,
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cost_dict=dict(
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cost_class=1,
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cost_bbox=5,
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cost_giou=2,
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),
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weight_dict=dict(
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loss_ce=1,
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loss_bbox=5,
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loss_giou=2,
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)))
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