Computer_Vision/Chapter04/Time_comparison_of_augmentation_scenario.ipynb

from torchvision import datasets
import torch
data_folder = '/content/' # This can be any directory you want to download FMNIST to
fmnist = datasets.FashionMNIST(data_folder, download=True, train=True)

tr_images = fmnist.data
tr_targets = fmnist.targets

val_fmnist = datasets.FashionMNIST(data_folder, download=True, train=False)
val_images = val_fmnist.data
val_targets = val_fmnist.targets

from imgaug import augmenters as iaa
aug = iaa.Sequential([
              iaa.Affine(translate_px={'x':(-10,10)}, mode='constant'),
            ])

%%time
for i in range(32):
  aug.augment_image(tr_images[i])

CPU times: user 85.4 ms, sys: 0 ns, total: 85.4 ms
Wall time: 85.9 ms

%%time
x = aug.augment_images(tr_images[:32])

CPU times: user 11.7 ms, sys: 0 ns, total: 11.7 ms
Wall time: 12.3 ms