Hello guys,
I am working on Image classification on the German Traffic Sign Dataset on Google Colab with Pytorch.
Here is the structure of the dataset:

GTSRB

Training

00000/

*.ppmm


…
00043/

*.ppmm




Test

*.ppmm
…
labels.csv





I have managed to upload the whole dataset to my drive(it took a long time!!!).
I have used ImageFolder class and Dataset class to load respectively training and test images.
However, Training my model is really slow, and GPU is not used efficiently. After many searches, I discovered that file transfer from drive to Colab is at fault here.
Does anyone know how I can use hd5 dataset (or others techniques) to first store all training and test images for later preprocessing?