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model = dict( |
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type='GroupFree3DNet', |
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data_preprocessor=dict(type='Det3DDataPreprocessor'), |
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backbone=dict( |
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type='PointNet2SASSG', |
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in_channels=3, |
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num_points=(2048, 1024, 512, 256), |
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radius=(0.2, 0.4, 0.8, 1.2), |
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num_samples=(64, 32, 16, 16), |
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sa_channels=((64, 64, 128), (128, 128, 256), (128, 128, 256), |
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(128, 128, 256)), |
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fp_channels=((256, 256), (256, 288)), |
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norm_cfg=dict(type='BN2d'), |
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sa_cfg=dict( |
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type='PointSAModule', |
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pool_mod='max', |
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use_xyz=True, |
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normalize_xyz=True)), |
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bbox_head=dict( |
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type='GroupFree3DHead', |
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in_channels=288, |
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num_decoder_layers=6, |
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num_proposal=256, |
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transformerlayers=dict( |
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type='BaseTransformerLayer', |
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attn_cfgs=dict( |
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type='GroupFree3DMHA', |
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embed_dims=288, |
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num_heads=8, |
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attn_drop=0.1, |
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dropout_layer=dict(type='Dropout', drop_prob=0.1)), |
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ffn_cfgs=dict( |
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embed_dims=288, |
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feedforward_channels=2048, |
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ffn_drop=0.1, |
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act_cfg=dict(type='ReLU', inplace=True)), |
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operation_order=('self_attn', 'norm', 'cross_attn', 'norm', 'ffn', |
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'norm')), |
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pred_layer_cfg=dict( |
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in_channels=288, shared_conv_channels=(288, 288), bias=True), |
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sampling_objectness_loss=dict( |
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type='mmdet.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=8.0), |
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objectness_loss=dict( |
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type='mmdet.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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center_loss=dict( |
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type='mmdet.SmoothL1Loss', reduction='sum', loss_weight=10.0), |
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dir_class_loss=dict( |
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type='mmdet.CrossEntropyLoss', reduction='sum', loss_weight=1.0), |
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dir_res_loss=dict( |
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type='mmdet.SmoothL1Loss', reduction='sum', loss_weight=10.0), |
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size_class_loss=dict( |
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type='mmdet.CrossEntropyLoss', reduction='sum', loss_weight=1.0), |
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size_res_loss=dict( |
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type='mmdet.SmoothL1Loss', |
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beta=1.0, |
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reduction='sum', |
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loss_weight=10.0), |
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semantic_loss=dict( |
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type='mmdet.CrossEntropyLoss', reduction='sum', loss_weight=1.0)), |
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|
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train_cfg=dict(sample_mode='kps'), |
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test_cfg=dict( |
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sample_mode='kps', |
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nms_thr=0.25, |
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score_thr=0.0, |
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per_class_proposal=True, |
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prediction_stages='last')) |
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