maskformer_swin_large_ade20k_512x512_160k.yml

_base_: 'maskformer_swin_tiny_ade20k_512x512_160k.yml'

train_dataset:
  type: ADE20K
  dataset_root: data/ADEChallengeData2016/
  transforms: 
    - type: ResizeByShort
      short_size: [320, 384, 448, 512, 576, 640, 704, 768, 832, 896, 960, 1024, 1088, 1152, 1216, 1280, 1344]
      max_size: 2560
    - type: RandomPaddingCrop
      crop_size: [640, 640] 
    - type: RandomDistort
      brightness_range: 0.125
      brightness_prob: 1.0
      contrast_range: 0.5
      contrast_prob: 1.0
      saturation_range: 0.5
      saturation_prob: 1.0
      hue_range: 18
      hue_prob: 1.0
    - type: RandomHorizontalFlip
    - type: GenerateInstanceTargets
      num_classes: 150
      ignore_index: 255
    - type: Normalize
      mean: [0.485, 0.456, 0.406]
      std: [0.229, 0.224, 0.225]

model:
  type: MaskFormer
  num_classes: 150
  backbone:
    type: SwinTransformer_large_patch4_window7_384_maskformer
  pretrained: https://bj.bcebos.com/paddleseg/paddleseg/dygraph/ade20k/maskformer_ade20k_swin_large/pretrain/model.pdparams