I have a dataset that is already labeled with specific class names and it is saved on my Computer as:
Train Dataset :
- -5_1
- -5_2
- -5_3
- etc...
Where the subfolders(5_1, 5_2, etc.) are the classes of the images. I want to use semi-supervised training where both labeled and unlabeled images must be used. But I don’t know how to “erase” classes from my Dataset in order make them unlabeled and load them to my CNN. For the labeled images I use datasets.ImageFolder() and DataLoader() so I can load them for training. Thanks for the help! PS1: I thought to save them in a different folder named as “Unlabeled” but I am sure that this is gonna use the name of the folder as a new class and this is something that it’s gonna ruin the predictions in training as well in testing
PS2: I must inform you that in this specific time I can't use any other pretrained dataset as CIFAR or MNIST where they already have unlabeled data.
I tried to create my own dataset as a new class but I am confused to the point where I must delete the classes.
