Comparing Different Automatic Image Augmentation Methods in PyTorch
Read OriginalThis technical article compares four automatic image augmentation techniques—AutoAugment, RandAugment, AugMix, and TrivialAugment—available in PyTorch's torchvision library. It explains their role in reducing overfitting by artificially expanding training datasets and provides a performance comparison using a ResNet-18 model on a simple benchmark, along with code examples for implementation.
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