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
- 00000/
- Test
- *.ppmm
- …
- labels.csv
- Training
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?