If you have ever worked on a Computer Vision project, you might know that using augmentations to diversify the dataset is the best practice. On this page, we will:
Сover the Resize augmentation;
Check out its parameters;
See how Resize affects an image;
And check out how to work with Resize using Python through the Albumentations library.
Let’s get into it!
As the name suggests, this data augmentation changes the size of your image according to the set height and width parameters.
- Interpolation - used to specify the interpolation algorithm:
import albumentations as albu
from PIL import Image
transform = albu.augmentations.geometric.resize.Resize(200,200)
augmented_image = transform(image=figure)['image']