text: # model settings
  model = dict(
      type='GFL',
      pretrained=(
          'https://github.com/shinya7y/UniverseNet/releases/download/20.06/'
          'res2net50_v1b_26w_4s-3cf99910_mmdetv2.pth'),
      backbone=dict(
          type='Res2Net',
          depth=50,
          scales=4,
          base_width=26,
          num_stages=4,
          out_indices=(0, 1, 2, 3),
          frozen_stages=1,
          norm_cfg=dict(type='SyncBN', requires_grad=True),
          norm_eval=False,
          style='pytorch',
          dcn=dict(type='DCN', deform_groups=1, fallback_on_stride=False),
          stage_with_dcn=(False, False, False, True)),
      neck=[
          dict(
              type='FPN',
              in_channels=[256, 512, 1024, 2048],
              out_channels=256,
              start_level=1,
              add_extra_convs='on_output',
              num_outs=5),
          dict(
              type='SEPC',
              out_channels=256,
              stacked_convs=4,
              pconv_deform=False,
              lcconv_deform=True,
              ibn=True,  # please set imgs/gpu >= 4
              pnorm_eval=False,
              lcnorm_eval=False,
              lcconv_padding=1)
      ],
      bbox_head=dict(
          type='GFLSEPCHead',
          num_classes=80,
          in_channels=256,
          stacked_convs=0,
          feat_channels=256,
          anchor_generator=dict(
              type='AnchorGenerator',
              ratios=[1.0],
              octave_base_scale=8,
              scales_per_octave=1,
              strides=[8, 16, 32, 64, 128]),
          loss_cls=dict(
              type='QualityFocalLoss',
              use_sigmoid=True,
              beta=2.0,
              loss_weight=1.0),
          loss_dfl=dict(type='DistributionFocalLoss', loss_weight=0.25),
          reg_max=16,
          loss_bbox=dict(type='GIoULoss', loss_weight=2.0)))
  # training and testing settings
  train_cfg = dict(
      assigner=dict(type='ATSSAssigner', topk=9),
      allowed_border=-1,
      pos_weight=-1,
      debug=False)
  test_cfg = dict(
      nms_pre=1000,
      min_bbox_size=0,
      score_thr=0.05,
      nms=dict(type='nms', iou_threshold=0.6),
      max_per_img=100)
  