I am using pytorch to build DCGAN which i aim to train on custom dataset.
I have already posted a question on training DCGAN on small dataset, and of course answer was data augmentation.
But i have a problem. I am coding in PyTorch and i want to perform several different transfomrations on existing ImageFolder object which represents my loaded dataset.
Idea was to perform, lets say around 5 different transformations, and after performing each transformation i want to expand my dataset by adding the newly transformed images to it. Here is pseudo code:
list_of_transformations = ['random_crop','center_crop','color_jitter','mirror','grayscale'] dataset = ImageFolder('path_to_dataset') for t in list_of_transformations dataset += dataset.t()
I am guessing this might not be the best idea, or is even considered 'stupid', but i am new to Deep Learning and Python in general. Any help would be appreciated! Thank you in advance!