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- batch_size: 8
- iters: 1000
-
- train_dataset:
- type: Dataset
- dataset_root: data/mini_supervisely
- train_path: data/mini_supervisely/train.txt
- num_classes: 2
- transforms:
- - type: Resize
- target_size: [192, 192]
- - type: ResizeStepScaling
- scale_step_size: 0
- - type: RandomRotation
- - type: RandomPaddingCrop
- crop_size: [192, 192]
- - type: RandomHorizontalFlip
- - type: RandomDistort
- - type: RandomBlur
- prob: 0.3
- - type: Normalize
- mode: train
-
- val_dataset:
- type: Dataset
- dataset_root: data/mini_supervisely
- val_path: data/mini_supervisely/val.txt
- num_classes: 2
- transforms:
- - type: Resize
- target_size: [192, 192]
- - type: Normalize
- mode: val
-
- export:
- transforms:
- - type: Resize
- target_size: [192, 192]
- - type: Normalize
-
- optimizer:
- type: sgd
- momentum: 0.9
- weight_decay: 0.0005
-
- lr_scheduler:
- type: PolynomialDecay
- learning_rate: 0.0001
- end_lr: 0
- power: 0.9
-
- loss:
- types:
- - type: MixedLoss
- losses:
- - type: CrossEntropyLoss
- - type: LovaszSoftmaxLoss
- coef: [0.8, 0.2]
- coef: [1, 1, 1, 1]
-
- model:
- type: MobileSeg
- num_classes: 2
- backbone:
- type: MobileNetV3_large_x1_0 # out channels: [24, 40, 112, 160]
- pretrained: https://paddleseg.bj.bcebos.com/dygraph/backbone/mobilenetv3_large_x1_0_ssld.tar.gz
- cm_bin_sizes: [1, 2, 4]
- backbone_indices: [0, 1, 2, 3]
- cm_out_ch: 128
- arm_out_chs: [32, 64, 96, 128]
- seg_head_inter_chs: [16, 32, 32, 32]
- use_last_fuse: True
- pretrained: pretrained_models/human_pp_humansegv2_lite_192x192_pretrained/model.pdparams
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