Yolov5 Object Detection with OpenVINO™ Toolkit and Roboflow!

In this notebook, we walk through how to use OpenVINO to optimize and deploy a YOLOv5 model. We provide a step-by-step guide for setting up the OpenVINO environment, training a YOLOv5 model in Pytorch, optimizing the model with OpenVINO, and deploying the optimized model on a variety of hardware platforms. We also discuss the use of tools provided by OpenVINO for performance analysis and debugging. We will run inference on both Pytorch and OpenVINO backend, and demonstrate the performance benefits when the model is optimized with OpenVINO.