@dipam The patch does work now. However, when I run the following train command given in the baseline model repo:
./tools/dist_train.sh ./configs/segformer/segformer_mit-b5_8x1_1024x1024_160k_suadd.py 1 --deterministic
I get this error:
No such file or directory: 'data/suadd23/inputs/train'
I tried to fix this by moving all the images into a ‘train’ folder inside suadd23. But then I got another error:
No such file or directory: 'data/suadd23/inputs/val'
Now I could go ahead and split the images into train and val, but I might run into other errors. So before I do so, I need to know if I’m missing something (maybe some setup step) - could you please guide me on this?
The validation set is used for the public leaderboard, this set will be made public at a later stage in the competition as the test set is still in development by the organizers. So for now you have to make your own dataset split.
Did you use an 80-20 split? Just want to be sure, in order to ensure reproducibility of baseline results.
The baseline was trained on the training set shared, and the current dataset used for the leaderboard was used as validation. Hence, unfortunately until that set is made public (it will be a few weeks before the end of challenge when the actual test set is ready), its not possible to reproduce the results right now.