Intel® Loss Prevention Reference Package

Overview

As computer vision technology becomes more mainstream in industrial and retail settings, using it for loss prevention is becoming increasingly complex. These vision workloads are substantial and require multiple stages of processing. For example, a typical loss prevention pipeline might capture video data, define regions of interest, implement tracking to monitor which products customers interact with, analyze the data using models like YOLOv5 and EfficientNet, and then post-process it to generate metadata that highlights which products are being purchased or potentially stolen. This is just one example of how such models and workflows can be utilized.

Implementing loss prevention solutions in retail isn't straightforward. Retailers, independent software vendors (ISVs), and system integrators (SIs) need a solid understanding of both hardware and software, as well as the costs involved in setting up and scaling these systems. Given the data-intensive nature of vision workloads, systems must be carefully designed, built, and deployed with numerous considerations in mind. Effectively combating shrinkage requires the right mix of hardware, software, and optimized configurations.

The Intel® Loss Prevention Reference Package is designed to help with this. It provides the essential components needed to develop and deploy a loss prevention solution using Intel® hardware, software, and open-source tools. This reference implementation includes a pre-configured pipeline that's optimized for Intel® hardware, simplifying the setup of an effective computer vision-based loss prevention system for retailers.

Next Steps

To begin using the loss prevention solution you can follow the Getting Started Guide.