├── ./pretrained
    ├── resnet50.pth
    ├── resnet101.pth
    └── deeplabv2_resnet101_coco_pretrained.pth
    
├── [Your Pascal Path]
    ├── JPEGImages
    └── SegmentationClass    # replace the official folder with above augmented masks 
    
├── [Your Cityscapes Path]
    ├── gtFine               # replace the official folder with above class mapped masks 
    └── leftImg8bit

export semi_setting='pascal/1_8/split_0'

CUDA_VISIBLE_DEVICES=0,1 python -W ignore main.py \
  --dataset pascal --data-root [Your Pascal Path] \
  --batch-size 16 --backbone resnet50 --model deeplabv3plus \
  --labeled-id-path dataset/splits/$semi_setting/labeled.txt \
  --unlabeled-id-path dataset/splits/$semi_setting/unlabeled.txt \
  --pseudo-mask-path outdir/pseudo_masks/$semi_setting \
  --save-path outdir/models/$semi_setting

@article{yang2021st++,
  title={ST++: Make Self-training Work Better for Semi-supervised Semantic Segmentation},
  author={Yang, Lihe and Zhuo, Wei and Qi, Lei and Shi, Yinghuan and Gao, Yang},
  journal={arXiv preprint arXiv:2106.05095},
  year={2021}
}