solov2_r50_enhance_coco.yml

_BASE_: [
  '../datasets/coco_instance.yml',
  '../runtime.yml',
  '_base_/solov2_r50_fpn.yml',
  '_base_/optimizer_1x.yml',
  '_base_/solov2_light_reader.yml',
]
pretrain_weights:  https://paddledet.bj.bcebos.com/models/pretrained/ResNet50_vd_ssld_v2_pretrained.pdparams
weights: output/solov2_r50_fpn_3x_coco/model_final
epoch: 36
use_ema: true
ema_decay: 0.9998

ResNet:
  depth: 50
  variant: d
  freeze_at: 0
  freeze_norm: false
  norm_type: sync_bn
  return_idx: [0,1,2,3]
  dcn_v2_stages: [1,2,3]
  lr_mult_list: [0.05, 0.05, 0.1, 0.15]
  num_stages: 4

SOLOv2Head:
  seg_feat_channels: 256
  stacked_convs: 3
  num_grids: [40, 36, 24, 16, 12]
  kernel_out_channels: 128
  solov2_loss: SOLOv2Loss
  mask_nms: MaskMatrixNMS
  dcn_v2_stages: [2]
  drop_block: True

SOLOv2MaskHead:
  mid_channels: 128
  out_channels: 128
  start_level: 0
  end_level: 3
  use_dcn_in_tower: True

LearningRate:
  base_lr: 0.01
  schedulers:
  - !PiecewiseDecay
    gamma: 0.1
    milestones: [24, 33]
  - !LinearWarmup
    start_factor: 0.
    steps: 1000