s2anet.yml

architecture: S2ANet
pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet50_vd_ssld_v2_pretrained.pdparams
weights: output/s2anet_r50_fpn_1x_dota/model_final.pdparams


# Model Achitecture
S2ANet:
  backbone: ResNet
  neck: FPN
  head: S2ANetHead

ResNet:
  depth: 50
  variant: d
  norm_type: bn
  return_idx: [1,2,3]
  num_stages: 4

FPN:
  in_channels: [256, 512, 1024]
  out_channel: 256
  spatial_scales: [0.25, 0.125, 0.0625]
  has_extra_convs: True
  extra_stage: 2
  relu_before_extra_convs: False

S2ANetHead:
  anchor_strides: [8, 16, 32, 64, 128]
  anchor_scales: [4]
  anchor_ratios: [1.0]
  anchor_assign: RBoxAssigner
  stacked_convs: 2
  feat_in: 256
  feat_out: 256
  align_conv_type: 'AlignConv'  # AlignConv Conv
  align_conv_size: 3
  use_sigmoid_cls: True
  reg_loss_weight: [1.0, 1.0, 1.0, 1.0, 1.1]
  cls_loss_weight: [1.1, 1.05]
  nms_pre: 2000
  nms:
    name: MultiClassNMS
    keep_top_k: -1
    score_threshold: 0.05
    nms_threshold: 0.1
    normalized: False

RBoxAssigner:
  pos_iou_thr: 0.5
  neg_iou_thr: 0.4
  min_iou_thr: 0.0
  ignore_iof_thr: -2