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:
Let’s jump in.
To define the term, Center Crop is a data augmentation technique that helps researchers to crop images to a specified height and width with a certain probability.
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.CenterCrop(200,200,p=0.5)#set height, width, and probability
image = np.array(Image.open('/some/image/file/path'))
image = transform(image=image)['image']
# Now the image is cropped and ready to be accepted by the model
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