PyRetri: A PyTorch-based Library for Unsupervised Image Retrieval by Deep Convolutional Neural Networks
This library addresses a gap for researchers in computer vision by offering a first-of-its-kind platform for unsupervised image retrieval, though it is incremental as it consolidates existing methods.
The authors tackled the lack of a unified software library for deep learning-based unsupervised image retrieval by introducing PyRetri, an open-source PyTorch library that encapsulates the retrieval process in stages and provides high usability and extensibility.
Despite significant progress of applying deep learning methods to the field of content-based image retrieval, there has not been a software library that covers these methods in a unified manner. In order to fill this gap, we introduce PyRetri, an open source library for deep learning based unsupervised image retrieval. The library encapsulates the retrieval process in several stages and provides functionality that covers various prominent methods for each stage. The idea underlying its design is to provide a unified platform for deep learning based image retrieval research, with high usability and extensibility. To the best of our knowledge, this is the first open-source library for unsupervised image retrieval by deep learning.