Legacy tutorial · Python · Version 0.1.0
NVIDIA Holoscan Bootcamp lab materials
Holoscan Bootcamp Jupyter notebook for self-paced learning of Holoscan core concepts
| Authors | Denis Leshchev (NVIDIA), Adam Thompson (NVIDIA), Nicolas Lebovitz (NVIDIA) |
|---|---|
| Supported platforms | x86_64, aarch64 |
| Language | Python |
| Version | 0.1.0 |
| Compatibility | HSDK 2.3 |
| Contribution level | Level 1 · Very high-quality code |
| Source | HoloHub |
Legacy HoloHub tutorial
This tutorial comes from HoloHub and was last tested with Holoscan SDK (HSDK) 2.3.
Overview
This is a meta-tutorial for deploying and running NVIDIA Holoscan Bootcamp lab materials.
Description
NVIDIA Holoscan Bootcamp was conducted by the NVIDIA team in collaboration with OpenHackathons on September 24th, 2024 (event link). The bootcamp included a lecture and a hands-on Python-based lab. The lab materials are freely available for downloading at OpenHackathons repo.
NVIDIA Holoscan Bootcamp lab materials include a Jupyter notebook for self-paced studying of the core Holoscan concepts.
The notebook covers the following topics:
- Creating custom Holoscan operators
- Connecting operators to form an application
- Build Holoscan applications with GPU-accelerated Python packages
- How to build a sensor to visualization pipeline
- Measuring and optimizing application performance
- How to build complex sensor processing workflows using multiple fragments and the advanced schedulers
The notebook guides users through the topics with example code and diagrams, and includes exercises to help them practice the concepts they've learned.
To run the lab materials, clone the repo and follow the deployment guide.