dim-vgg16.yml

batch_size: 16
iters: 100000

train_dataset:
  type: MattingDataset
  dataset_root: data/PPM-100
  train_file: train.txt
  transforms:
    - type: LoadImages
    - type: RandomCropByAlpha
      crop_size: [[320, 320], [480, 480], [640, 640]]
    - type: Resize
      target_size: [320, 320]
    - type: RandomDistort
    - type: RandomBlur
    - type: RandomHorizontalFlip
    - type: Normalize
  mode: train
  get_trimap: True

val_dataset:
  type: MattingDataset
  dataset_root: data/PPM-100
  val_file: val.txt
  transforms:
    - type: LoadImages
    - type: LimitLong
      max_long: 3840
    - type: Normalize
  mode: val
  get_trimap: True

model:
  type: DIM
  backbone:
    type: VGG16
    input_channels: 4
    pretrained: https://paddleseg.bj.bcebos.com/matting/models/DIM_VGG16_pretrained/model.pdparams
  pretrained: Null

optimizer:
  type: adam

learning_rate:
  value: 0.001