So the story is that I am doing a building segmentation for various sites. This means that I need to randomly split the train val test to equal proportion (e.g. to ratio of 60%, 20%, 10% respectively) for different location, and subsequently concatenating them into a big dataset.
I have manage to first split the images and then match the label to them. However, I’ve found out that once I concatenated the datasets together, although both resulting pytorch datasets of image and label contain both the correct images and labels, they are not in the same order. I am struggling to find a way to match and sort the order within the pytorch dataset object or pytorch dataloader object. Have anyone had similar issues before:
See attached output of print(Train.png_dir, Train.lbl_dir) in the same Train <pytorch.dataset> object:
The folder structure indicates the location:
KBY = Kalobeyei
DZK = Dzaleka
DZKN = Dzaleka North
I assume this means the labels do not correspond to the right sample anymore?
If so, how did you concatenate the data and made sure the correspondence is not broken?
Assuming you are using a custom Dataset, I guess you’ve created the data/label arrays in the __init__?
