Omniverse Replicator augments costly, laborious human-labeled real-world data, which can be error prone and incomplete, with the ability to create large and diverse physically accurate data tailored to the needs of autonomous vehicle and robotics developers. It also enables generating ground-truth data that's difficult or impossible for humans to label, such as velocity, depth, occluded objects, adverse weather conditions, or tracking the movement of objects across sensors. In this training lab, you'll learn to generate a synthetic dataset from assets and scenes using Omniverse Replicator in a hands-on GPU environment. By participating in this training lab, you’ll learn the following topics: The case for synthetic data How to place a target asset in randomized environments to create a dataset How to turn the dataset into annotated data for training your own model
Prerequisite(s):
Please disregard any reference to "Event Code" for access to training materials. "Event Codes" are only valid during the original live session. Explore more training options offered by the NVIDIA Deep Learning Institute (DLI). Choose from an extensive catalog of self-paced, online courses or instructor-led virtual workshops to help you develop key skills in AI, HPC, graphics & simulation, and more.