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- architecture: SparseRCNN
- pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet50_cos_pretrained.pdparams
- SparseRCNN:
- backbone: ResNet
- neck: FPN
- head: SparseRCNNHead
- postprocess: SparsePostProcess
- ResNet:
- # index 0 stands for res2
- depth: 50
- norm_type: bn
- freeze_at: 0
- return_idx: [0,1,2,3]
- num_stages: 4
- FPN:
- out_channel: 256
- SparseRCNNHead:
- head_hidden_dim: 256
- head_dim_feedforward: 2048
- nhead: 8
- head_dropout: 0.0
- head_cls: 1
- head_reg: 3
- head_dim_dynamic: 64
- head_num_dynamic: 2
- head_num_heads: 6
- deep_supervision: true
- num_proposals: 100
- loss_func: SparseRCNNLoss
- SparseRCNNLoss:
- losses: ["labels", "boxes"]
- focal_loss_alpha: 0.25
- focal_loss_gamma: 2.0
- class_weight: 2.0
- l1_weight: 5.0
- giou_weight: 2.0
- SparsePostProcess:
- num_proposals: 100
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