End-to-End Multimodal Data Augmentation and Adversarial Robustness Benchmark with AugLy for Images, Text, Audio, and PyTorch

The article presents a tutorial demonstrating a multimodal augmentation and robustness workflow using AugLy for images, text, and audio. It covers AugLy's functional and class-based APIs, metadata and intensity tracking, probabilistic composition, bounding-box-aware transformations, and custom transforms. Robustness experiments include benchmarking perceptual-hash copy detection under image distortions and evaluating text classifiers against adversarial perturbations and Unicode obfuscation. The workflow integrates audio augmentation and connects AugLy transformations to PyTorch datasets and DataLoaders.