With the advent of specialized hardware such as Graphics Processing Units (GPUs), large scale image localization, classification and retrieval have seen increased prevalence. Designing scalable software architecture that co-evolves with such specialized hardware is a challenge in the commercial setting. In this paper, we describe one such architecture (\textit{Cortexica}) that leverages scalability of GPUs and sandboxing offered by docker containers. This allows for the flexibility of mixing different computer architectures as well as computational algorithms with the security of a trusted environment. We illustrate the utility of this framework in a commercial setting i.e., searching for multiple products in an image by combining image localisation and retrieval.
@article{arxiv.1703.02898,
title = {Large-scale image analysis using docker sandboxing},
author = {B Sengupta and E Vazquez and M Sasdelli and Y Qian and M Peniak and L Netherton and G Delfino},
journal= {arXiv preprint arXiv:1703.02898},
year = {2017}
}