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stdc1_seg_pssl.yml
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stdc1_seg_pssl.yml
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# img_nums = 1281121, bs=12*8, iters=13345*10, so epoch = 10
# img_nums = 1281121, bs=10*8, iters=16014*10, so epoch = 10
batch_size: 12
iters: 133450
train_dataset:
type: PSSLDataset
imagenet_root: data/ImageNet_org
pssl_root: data/pssl2.1_consensus
transforms:
- type: ResizeByShort
short_size: 256
- type: ResizeStepScaling
min_scale_factor: 0.5
max_scale_factor: 2.0
scale_step_size: 0
- type: RandomPaddingCrop
crop_size: [256, 256]
label_padding_value: 1001
- type: RandomHorizontalFlip
- type: RandomDistort
brightness_range: 0.2
contrast_range: 0.2
saturation_range: 0.2
- type: Normalize
mode: train
optimizer:
type: SGD
momentum: 0.9
weight_decay: 4.0e-5
lr_scheduler:
type: StepDecay
learning_rate: 0.01
step_size: 2500000
model:
type: STDCSeg
backbone:
type: STDC1
relative_lr: 0.1
pretrained: https://bj.bcebos.com/paddleseg/dygraph/STDCNet1.tar.gz
pretrained: null
num_classes: 1001
loss:
types:
- type: CrossEntropyLoss
weight: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 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coef: [1, 1, 1]