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pp_mobileseg_base_cityscapes_1024x512_80k.yml
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pp_mobileseg_base_cityscapes_1024x512_80k.yml
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_base_: '../_base_/cityscapes.yml'
batch_size: 16 # total batch size is 32
iters: 80000
train_dataset:
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
optimizer:
_inherited_: False
type: AdamW
weight_decay: 0.01
custom_cfg:
- name: pos_embed
weight_decay_mult: 0.0
- name: head
lr_multi: 10.0
- name: bn
weight_decay_mult: 0.0
lr_scheduler:
type: PolynomialDecay
learning_rate: 0.0006
end_lr: 0
power: 1.0
warmup_iters: 1500
warmup_start_lr: 1.0e-6
loss:
types:
- type: MixedLoss
losses:
- type: CrossEntropyLoss
- type: LovaszSoftmaxLoss
coef: [0.8, 0.2]
coef: [1]
model:
type: PPMobileSeg
num_classes: 19
backbone:
type: MobileSeg_Base
inj_type: AAMSx8
out_feat_chs: [64, 128, 192]
pretrained: https://bj.bcebos.com/paddleseg/dygraph/ade20k/pp_mobileseg/pretrain/model.pdparams
upsample: intepolate # During exportation, you need to change it to vim for using VIM