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46 lines
1.2 KiB
Python
46 lines
1.2 KiB
Python
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# model settings
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model = dict(
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type='Detection',
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pretrained=
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'http://pai-vision-data-hz.oss-cn-zhangjiakou.aliyuncs.com/pretrained_models/easycv/resnet/torchvision/resnet50.pth',
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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={
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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={
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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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))
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