mask_rcnn_res2net50_vd_26w_4s_fpn_2x_coco.yml

_BASE_: [
  '../datasets/coco_instance.yml',
  '../runtime.yml',
  '../mask_rcnn/_base_/optimizer_1x.yml',
  '../mask_rcnn/_base_/mask_rcnn_r50_fpn.yml',
  '../mask_rcnn/_base_/mask_fpn_reader.yml',
]
pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/Res2Net50_vd_26w_4s_pretrained.pdparams
weights: output/mask_rcnn_res2net50_vd_26w_4s_fpn_2x_coco/model_final

MaskRCNN:
  backbone: Res2Net
  neck: FPN
  rpn_head: RPNHead
  bbox_head: BBoxHead
  mask_head: MaskHead
  # post process
  bbox_post_process: BBoxPostProcess
  mask_post_process: MaskPostProcess


Res2Net:
  # index 0 stands for res2
  depth: 50
  width: 26
  scales: 4
  norm_type: bn
  freeze_at: 0
  return_idx: [0,1,2,3]
  num_stages: 4
  variant: d


epoch: 24
LearningRate:
  base_lr: 0.01
  schedulers:
  - !PiecewiseDecay
    gamma: 0.1
    milestones: [16, 22]
  - !LinearWarmup
    start_factor: 0.3333333333333333
    steps: 500


TrainReader:
  batch_size: 2