text: _base_ = "./gfl_r50_fpn_1x_coco.py"
  # learning policy
  lr_config = dict(step=[16, 22])
  total_epochs = 24
  # multi-scale training
  img_norm_cfg = dict(
      mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True
  )
  train_pipeline = [
      dict(type="LoadImageFromFile"),
      dict(type="LoadAnnotations", with_bbox=True),
      dict(
          type="Resize",
          img_scale=[(1333, 480), (1333, 800)],
          multiscale_mode="range",
          keep_ratio=True,
      ),
      dict(type="RandomFlip", flip_ratio=0.5),
      dict(type="Normalize", **img_norm_cfg),
      dict(type="Pad", size_divisor=32),
      dict(type="DefaultFormatBundle"),
      dict(type="Collect", keys=["img", "gt_bboxes", "gt_labels"]),
  ]
  data = dict(train=dict(pipeline=train_pipeline))
  