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Albumentations is an image augmentation library and computer vision preprocessing tool designed to expand datasets for deep learning models. It provides a collection of transformations that modify pixel values and spatial geometry to increase the diversity of training samples and improve model generalization. The library supports both 2D image augmentation and 3D volumetric data augmentation. It handles a variety of labels alongside images, ensuring that bounding boxes, keypoints, and segmentation masks remain accurately aligned when spatial transformations are applied. The tool incorporates
A framework for large scale recommendation algorithms.
TensorFlow Recommenders is a library for building recommender system models using TensorFlow.
The main features of tensorflow/recommenders are: Deep Learning Frameworks, Recommender Systems.
Projects with overlapping indexed features include: alankbi/detecto — Build fully-functioning computer vision models with PyTorch. albu/albumentations — Albumentations is an image augmentation library and computer vision preprocessing tool designed to expand datasets for… alibaba/easyrec — A framework for large scale recommendation algorithms. allegro/allrank — allRank is a framework for training learning-to-rank neural models based on PyTorch. alrojo/tensorflow-tutorial — Practical tutorials and labs for TensorFlow used by Nvidia, FFN, CNN, RNN, Kaggle, AE. 5vision/darqn — Deep Attention Recurrent Q-Network.
