This tutorial explains how to use a classification model to identify the content of an image based on the categories it was trained to recognize.
The first section instructs you on how to run the scripts and training data (images of cats and dogs) that are included in the VM to create a classification model. The second section tells you how to create a classification model from your own training data.
The model training workflow recommended by LUCID involves training a model on Google Cloud Platform (GCP), downloading the model to your local PC, and then using Triton Smart with this local PC.
Download the Triton Smart Support Package from the Triton Smart product page for compiled Windows applications for displaying the inference results.