Deploying A Custom Image Classifier On An Oak-d

In this tutorial, you will learn how to deploy an image classification model trained in the TensorFlow framework on the OAK-D device. The OpenVINO toolkit is used to convert and optimize the TensorFlow FP32 (32-bit floating point) model to the MyriadX blob file format expected by the Visual Processing Unit of the OAK device. The converted blob file is then used to run image classification inference on the OAK-D using the DepthAI API. This tutorial is the last in a 4-part series on OAK-101.