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]