Performance gap and issue in code

[suikei-wang]

Hi there,

Thanks for the work! I trained this SSL model for semi-supervised domain adaptation semantic segmentation. I used the label ratio of 1/30, trained on the GTA5 dataset as the full labelled dataset and Cityscapes as the partially labelled dataset. Evaluated on Cityscapes val set. I kept all configs as the same as the descriptions in your supplementary material. Here are the results I got from my training on a single NVIDIA GeForce RTX 3090:

label ratio	mIoU	Road	Sidewalk	Building	Wall	Fence	Pole	Traffic light	Traffic sign	Vegetartion	Terrain	Sky	Person	Rider	Car	Truck	Bus	Train	Motorcycle	Bicycle
1/30	51.8	94.8	65.7	85.4	369	32.6	35.3	38.8	47.5	86.1	47.1	89.4	61.5	35.4	86.2	33.9	0.59	21.68	29.55	56.51

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Besides, there is a variable best_mIoU_improved which is not defined but used to compare with best_mIoU in the code. Is that any improvement made here?

Thanks.