Overview
TorchVision Transforms is a module within PyTorch designed to facilitate common computer vision tasks by providing a suite of data transformation tools. It supports operations on images (both PIL images and tensors), videos, bounding boxes, segmentation masks, and keypoints. The transforms are crucial for data augmentation, enabling the creation of diverse training datasets, which improves model generalization. The v2 transforms offer significant performance improvements over v1 and support a wider range of data types and input structures, including lists, dicts, and tuples. These transforms are easily integrated into data loading pipelines, making them an essential component for building robust and accurate computer vision models.