How do I preprocess images for PyTorch vision models?

How do I preprocess images for PyTorch vision models?

To preprocess images for PyTorch, you typically use the torchvision.transforms module. This includes resizing, normalization, and data augmentation.

Can you give me an example of how to use transforms?

Sure! Here's a simple example:

from torchvision import transforms

transform = transforms.Compose([
    transforms.Resize((256, 256)),
    transforms.ToTensor(),
    transforms.Normalize(mean=[0.5, 0.5, 0.5], std=[0.5, 0.5, 0.5])
])

What does normalization do in this context?

Normalization scales the pixel values to a range that helps the model learn better. It typically centers the data around zero.

Are there any common data augmentation techniques I should know about?

Yes! Common techniques include random horizontal flips, rotations, and color jittering. These help improve model robustness.