albumentationsRepository32/100 via “bounding box-aware geometric transformations”
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: Implements coordinate transformation matrices that propagate through geometric operations, automatically handling bbox clipping and filtering without requiring manual recalculation; supports multiple bbox format standards (COCO, Pascal VOC, YOLO) via pluggable format converters
vs others: More robust than manual bbox transformation because it handles edge cases (clipping, filtering) automatically; more flexible than imgaug's bbox handling because it supports multiple annotation formats natively