architecture: TTFNet
pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet50_vd_ssld_pretrained.pdparams
norm_type: sync_bn
use_ema: true
ema_decay: 0.9998

TTFNet:
  backbone: ResNet
  neck: TTFFPN
  ttf_head: TTFHead
  post_process: BBoxPostProcess

ResNet:
  depth: 50
  variant: d
  return_idx: [0, 1, 2, 3]
  freeze_at: -1
  norm_decay: 0.
  variant: d
  dcn_v2_stages: [1, 2, 3]

TTFFPN:
  planes: [256, 128, 64]
  shortcut_num: [3, 2, 1]

TTFHead:
  dcn_head: true
  hm_loss:
    name: CTFocalLoss
    loss_weight: 1.
  wh_loss:
    name: GIoULoss
    loss_weight: 5.
    reduction: sum

BBoxPostProcess:
  decode:
    name: TTFBox
    max_per_img: 100
    score_thresh: 0.01
    down_ratio: 4