batch_size: 4 iters: 160000 train_dataset: type: Dataset dataset_root: datasets/Cityscapes train_path: datasets/Cityscapes/train.txt num_classes: 19 transforms: - type: ResizeStepScaling min_scale_factor: 0.125 max_scale_factor: 1.5 scale_step_size: 0.125 - type: RandomPaddingCrop crop_size: [1024, 512] - type: RandomHorizontalFlip - type: RandomDistort brightness_range: 0.5 contrast_range: 0.5 saturation_range: 0.5 - type: Normalize mode: train val_dataset: type: Dataset dataset_root: datasets/Cityscapes val_path: datasets/Cityscapes/val.txt num_classes: 19 transforms: - type: Normalize mode: val model: type: PPLiteSeg backbone: type: STDC1 pretrained: https://bj.bcebos.com/paddleseg/dygraph/PP_STDCNet1.tar.gz arm_out_chs: [32, 64, 128] seg_head_inter_chs: [32, 64, 64] optimizer: type: SGD momentum: 0.9 weight_decay: 5.0e-4 lr_scheduler: type: PolynomialDecay learning_rate: 0.005 end_lr: 0 power: 0.9 warmup_iters: 1000 warmup_start_lr: 1.0e-5 loss: types: - type: OhemCrossEntropyLoss min_kept: 130000 # batch_size * 1024 * 512 // 16 - type: OhemCrossEntropyLoss min_kept: 130000 - type: OhemCrossEntropyLoss min_kept: 130000 coef: [1, 1, 1] test_config: aug_eval: True scales: 0.5