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image-matting-app
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batch_size: 16
iters: 100000

train_dataset:
  type: MattingDataset
  dataset_root: data/PPM-100
  train_file: train.txt
  transforms:
    - type: LoadImages
    - type: RandomCrop
      crop_size: [512, 512]
    - type: RandomDistort
    - type: RandomBlur
    - type: RandomHorizontalFlip
    - type: Normalize
  mode: train

val_dataset:
  type: MattingDataset
  dataset_root: data/PPM-100
  val_file: val.txt
  transforms:
    - type: LoadImages
    - type: ResizeByShort
      short_size: 512
    - type: ResizeToIntMult
      mult_int: 32
    - type: Normalize
  mode: val
  get_trimap: False

model:
  type: MODNet
  backbone:
    type: MobileNetV2
    # pretrained: https://paddleseg.bj.bcebos.com/matting/models/MobileNetV2_pretrained/model.pdparams
  pretrained: Null

optimizer:
  type: sgd
  momentum: 0.9
  weight_decay: 4.0e-5

lr_scheduler:
  type: PiecewiseDecay
  boundaries: [40000, 80000]
  values: [0.02, 0.002, 0.0002]