Alternatively to @albanD’s solution, you could also use DatasetFolder, which basically is the underlying class of ImageFolder
.
Using this class you can provide your own files extensions and loader
to load the samples.
def npy_loader(path):
sample = torch.from_numpy(np.load(path))
return sample
dataset = datasets.DatasetFolder(
root='PATH',
loader=npy_loader,
extensions=['.npy']
)
If you want to use transformations, you would need to convert the sample tensors to PIL.Images
in your loader.