TTAch provides test-time augmentation techniques for deep learning models in computer vision tasks. During inference, it applies augmentations like flips, rotations, and scales to input images, passes them through the model, reverses the transformations, and merges predictions (via mean, max, or gmean) to improve accuracy. It offers specialized wrappers for segmentation, classification, and keypoint detection models, all integrated with PyTorch.