Hii,
I would like to do cross validation on my dataset.
Currently I have a binary classification network for medical images and having a 90% accuracy on my validation set. My validation image dataset is small, so i would like to do cross validation.
I am using a custom dataset class to load the dataset and the Folders are arranged in this way:
Train/1stclass
Train/2ndclass
Valid/1stClass
Valid/2ndclass
Should I mix them in one Folder for the Cross Validation?
I am new to pytorch,  Please if anyone can help me with this… I would really appreciate it … Thank You