Before you set up your image analysis project, please contact us through the SBDI Support Center. We will then plan your project together, give you access to the system, and help you getting started. Once, you have access, you can follow the notebook specified below. 

Once you have access to to the system you can use the notebook 01_Project_Setup.ipynb in the KSO repo to create and configure a personal project, attach a YOLO dataset and get ready for training.

This tutorial video guides you through the process of training and testing an object detection model using the SUBSIM notebooks available on the Digital Twin Ocean infrastructure EDITO. It will introduce you to the structure of input data, explain how to train a model, inspect the results and compare these against a stronger pre-trained model. IMPORTANT: This tutorial is using a demo workflow for training, while the original SUBSIM workflows on the GitHub pages above are more elaborate.