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:
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To define the term, Rotate is a data augmentation technique used to randomly rotate an image clockwise or counter-clockwise by a certain number of degrees. As the transformation result, you will get an updated image with the changed position of the objects in the frame.
Using Rotate helps Data Scientists increase the variety of points of view on an object in the training set. This approach creates the needed diversity without the need to find and label more data.
Hello, thank you for using the code provided by Hasty. Please note that some code blocks might not be 100% complete and ready to be run as is. This is done intentionally as we focus on implementing only the most challenging parts that might be tough to pick up from scratch. View our code block as a LEGO block - you can’t use it as a standalone solution, but you can take it and add to your system to complement it. If you have questions about using the tool, please get in touch with us to get direct help from the Hasty team.
import albumentations as albu
from PIL import Image
import numpy as np
transform = albu.RandomRotation(degrees=(-90,90))
image = np.array(Image.open('/some/random/image.png'))
augmented_image = transform(image=image)['image']
# We have the rotated image in augmented_image.
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