albumentationsRepository32/100 via “semantic segmentation mask augmentation with label preservation”
Fast, flexible, and advanced augmentation library for deep learning, computer vision, and medical imaging. Albumentations offers a wide range of transformations for both 2D (images, masks, bboxes, keypoints) and 3D (volumes, volumetric masks, keypoints) data, with optimized performance and seamless
Unique: Uses nearest-neighbor interpolation for mask resampling by default to prevent label bleeding, and supports multiple mask formats (single-channel class indices, multi-channel one-hot, multi-class) via pluggable format handlers
vs others: More robust than naive linear interpolation of masks because it preserves class label integrity; more flexible than torchvision because it handles multi-channel and one-hot encoded masks natively