Hi,
The dataset that the mmseg baseline model is trained on is split into train/validation according to this code:
+data = dict(
+ samples_per_gpu=2,
+ workers_per_gpu=2,
+ train=dict(
+ type=dataset_type,
+ data_root=data_root,
+ img_dir='inputs/train',
+ ann_dir='semantic_annotations/train',
+ pipeline=train_pipeline),
+ val=dict(
+ type=dataset_type,
+ data_root=data_root,
+ img_dir='inputs/val',
+ ann_dir='semantic_annotations/val',
+ pipeline=test_pipeline),
+ test=dict(
+ type=dataset_type,
+ data_root=data_root,
+ img_dir='inputs/val',
+ ann_dir='semantic_annotations/val',
+ pipeline=test_pipeline))
However, as when using the dataset download link it is not split into two folders “train” and “val” for both the inputs and masks. I have manually put them into a 84/16 split. Midway through my model training, I noticed that class “ANIMAL” and “SNOW” does not show up in the validation set.
Therefore, my questions are: how are they split in % and is it correct that the classes “ANIMAL” and “SNOW” are not present?