This repository provides a PyTorch implementation of the OLTR algorithm for large-scale long-tailed recognition in an open world. It addresses training classifiers on datasets with heavily imbalanced class distributions while also handling unknown or unseen classes at test time. The approach combines visual memory, meta embedding, and feature modulation techniques to improve performance on rare classes and unknown categories.