Analysis of the OWLv2 model usage for real-time object detection

The implementation of an AI-enabled video processing system for industry often faces a trade-off between accuracy, speed, cost, and safety. The authors present a plan and scheme of operation of an industrial AI system for searching objects in images in real time using only local budget solutions from the user segment. Introduction. This research describes the structure of an industrial scalable multi-camera system for detecting objects in a production environment based on text descriptors. The system is based on the OWLv2 (Open-World Localization Vision Transformer) model: a visual transformer for localizing objects in open space. Methods and materials. A video stream with various objects is used as objects, which must then be recognized and identified. The use of the open OWLv2 model and Nvidia's user-level GPU together with the microservices architecture allows you to create flexible software that can be scaled as the needs of the enterprise using a single local service that is completely isolated from the outside world. Such a service, among other things, will allow you to further implement advanced versions of models that solve complex problems, such as quality control of composites, without the need to significantly rebuild the service, while maintaining a single API. The system is designed to process real-time video streams and single images from multiple cameras in real time using graphics processing unit (GPU) acceleration, distributed task processing on Celery and RabbitMQ, centralized observability with Prometheus, Grafana and Loki. Results and discussion. The architecture prioritizes operational resilience, cost efficiency, and the ability to scale from two to a hundred cameras without a fundamental redesign. By adopting a decentralized, microservices approach from the outset, the project avoids the technical debt and refactoring burden that would arise from building a monolithic system and trying to distribute it later. Using MinIO, RabbitMQ, Prometheus, Loki, and Celery is a good choice for an industrial solution.