How to use QualityInspector STFPM to train multiple types of data in MvTec AD dataset at the same time?

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I use QualityInspector STFPM with MvTec AD dataset ,How to train both 'bottle' and 'cable' datasets?

'python tools/uad/stfpm/train.py --config ./configs/uad/stfpm/stfpm_resnet18_mvtec.yml --category bottle' This command can only train one dataset, not multiple datasets at the same time.

' python tools/uad/stfpm/train.py --config ./configs/uad/stfpm/stfpm_resnet18_mvtec.yml --category all' I get an error when using this command :

Traceback (most recent call last): File "tools/uad/stfpm/train.py", line 225, in main() File "tools/uad/stfpm/train.py", line 94, in main train_image_list, val_image_list = train_test_split( File "/home/zhaozihao/anaconda3/envs/PaddlePaddle_other/lib/python3.8/site-packages/sklearn/utils/_param_validation.py", line 211, in wrapper return func(*args, **kwargs) File "/home/zhaozihao/anaconda3/envs/PaddlePaddle_other/lib/python3.8/site-packages/sklearn/model_selection/_split.py", line 2617, in train_test_split n_train, n_test = _validate_shuffle_split( File "/home/zhaozihao/anaconda3/envs/PaddlePaddle_other/lib/python3.8/site-packages/sklearn/model_selection/_split.py", line 2273, in _validate_shuffle_split raise ValueError( ValueError: With n_samples=0, test_size=0.2 and train_size=None, the resulting train set will be empty. Adjust any of the aforementioned parameters.

I see category variable can be set [textures, objects, all],but i don't konw how to use.
Who can tell me how to use ? Thanks!