Hi everyone,
I have a dataset with 885 images and I have to perform data augmentation generating 3000 training examples for each image by random translation and random rotation. However since the dataset would increase too much and I cannot store all the images on the disk. I know that I can perform transform ‘on the fly’ but I need to create the augment the dataset and then train the complete dataset.
Is there a way to augment data and save augmented ‘dataLoader’ in separate files, use another process to load the saved ‘dataloaders’ and train the network with all the examples?