deeplabv3_resnet50_os8_uwmgi_256x256_80k_withaux.yml

_base_: '../_base_/uwmgi.yml'

batch_size: 8
iters: 80000

train_dataset:
  transforms:
    - type: AddMultiLabelAuxiliaryCategory
    - type: Resize
      target_size: [256, 256]
    - type: RandomHorizontalFlip
    - type: RandomVerticalFlip
    - type: RandomDistort
      brightness_range: 0.4
      contrast_range: 0.4
      saturation_range: 0.4
    - type: Normalize
      mean: [0.0, 0.0, 0.0]
      std: [1.0, 1.0, 1.0]
  num_classes: 4

val_dataset:
  transforms:
    - type: AddMultiLabelAuxiliaryCategory
    - type: Resize
      target_size: [256, 256]
    - type: Normalize
      mean: [0.0, 0.0, 0.0]
      std: [1.0, 1.0, 1.0]
  num_classes: 4

model:
  type: DeepLabV3
  num_classes: 4
  backbone:
    type: ResNet50_vd
    output_stride: 8
    multi_grid: [1, 2, 4]
    pretrained: https://bj.bcebos.com/paddleseg/dygraph/resnet50_vd_ssld_v2.tar.gz
  backbone_indices: [3]
  aspp_ratios: [1, 12, 24, 36]
  aspp_out_channels: 256
  align_corners: False
  pretrained: null