Holoscan Reference Applications

Visit https://nvidia-holoscan.github.io/holohub for a searchable catalog of all available components.

This is a central repository for the NVIDIA Holoscan AI sensor processing community to share reference applications, operators, tutorials and benchmarks. We invite users and developers of the Holoscan platform to reuse and contribute to this repository.

Overview

This repository is a collection of applications and extensions created by the Holoscan AI sensor processing community. The following directories make up the core of this repo:

Example applications: Visit applications to explore an evolving collection of example applications built on the NVIDIA Holoscan platform. Examples are available from NVIDIA, partners, and community collaborators, and provide a demonstration of the SDK capabilities.
Community components: Visit operators and gxf_extensions to explore reusable Holoscan modules.
Package configurations: Visit pkg for a list of Debian packages to generate, to distribute operators and applications for easier development.
Tutorials: Visit tutorials for extended walkthroughs and tips for the Holoscan platform.
Benchmarks: Visit benchmarks for performance benchmarks, tools, and examples to evaluate the performance of Holoscan applications.

Visit the Holoscan SDK User Guide to learn more about the NVIDIA Holoscan AI sensor processing platform. You can also chat with the Holoscan-GPT Large Language Model to learn about using Holoscan SDK, ask questions, and get code help. Holoscan-GPT requires an OpenAI account.

Prerequisites

Supported Platforms

You will need a platform supported by NVIDIA Holoscan SDK. Refer to the Holoscan SDK User Guide for the latest requirements. In general, Holoscan supported platforms include:

An x64 PC with an Ubuntu operating system and an NVIDIA GPU; or
A supported NVIDIA ARM development kit.

Individual examples and operators in this repo may have additional platform requirements. For instance, some examples may support only ARM platforms.

Build Environment

You may choose to build applications and operators in a containerized development environment or in your native environment.

We strongly recommend new users follow our Container Build instructions to set up a container for development.

If you prefer to build locally without docker, take a look at our Native Build instructions.

Once your development environment is configured you may move on to Building the Holohub components you are interested in.

NOTE: Several applications and operators require additional dependencies beyond the basic prerequisites listed above. Please refer to the README of the specific application or operator for detailed dependency information before attempting to build or run it.

Container Build (Recommended)

Software Prerequisites

To build and run in a containerized environment you will need:

the NVIDIA Container Toolkit (v1.12.2 or later)
Docker, including the buildx plugin (docker-buildx-plugin)
git version control
(optional) Python 3.10+ on the host machine to run the holohub infrastructure script

You will also need to set up your NVIDIA NGC credentials at ngc.nvidia.com.

Fetch

Clone the repository to your local system:

git clone https://www.github.com/nvidia-holoscan/holohub.git
cd holohub

Alternatively, download sources as a ZIP archive from the GitHub homepage.

HoloHub run command (recommended)

The easiest way to build and run Holohub applications is to use the ./holohub run command.

./holohub run <application_name>

If you want to use a specific based image for the application, you can use the --base-img option.

./holohub run --base-img <base_image> <application_name>

NOTE: The build_and_run command is not supported for all applications and operators, especially applications that requires manual configurations or applications that requires additional datasets. Please refer to the README of each application or operator for more information.

If you want a more detailed command to build and run a specific application, please follow the instructions below.

Build

Holohub provides a default development container that can be used to build and run applications. However several applications and operator requires specific dependencies that are not available in the default development container and are provided by specific docker files. Please refer to the README of each application or operator for more information.

Run the following command to build the development container for a given project. The build may take a few minutes.

./holohub build-container [project_name]

For Holoscan SDK v3.6.1 and later, you can specify the CUDA version using the --cuda option (e.g., --cuda 12 or --cuda 13), which automatically selects the appropriate container tag and passes the CUDA version as a build argument.

Check to verify that the image is created:

$ docker images
REPOSITORY      TAG               IMAGE ID       CREATED         SIZE
...
holohub         ngc-v3.5.0-dgpu   c93e9f90a263   1 minutes ago   19.1GB
...

Note: The holohub command line program will by default detect if the system is using an iGPU (integrated GPU) or a dGPU (discrete GPU) and use NGC's Holoscan SDK container for the Container build. See Advanced Container Build Options if you would like to use an older version of the SDK as a custom base image.

See the Developer Reference document for additional options.

Launch

Launch the Docker container environment:

./holohub run-container [my_project]

You are now ready to build Holohub operators, applications, or packages!

Note The run-container option will use the default development container built using Holoscan SDK's container from NGC for the local GPU. The script will also inspect for available video devices (V4L2, AJA capture boards, Deltacast capture boards) and the presence of Deltacast's Videomaster SDK and map it into the development container.

Platform Notes (Container)

The development container has been tested on the following platforms:

x86_64 workstation with multiple RTX GPUs
Clara AGX Dev Kit (dGPU mode)
IGX Orin Dev Kit (dGPU and iGPU mode)
AGX Orin Dev Kit (iGPU)

Notes for AGX Orin Dev Kit:

(1) On AGX Orin Dev Kit the launch script will add --privileged and --group-add video to the docker run command for the reference applications to work. Please also make sure that the current user is member of the group video.

(2) When building Holoscan SDK on AGX Orin Dev Kit from source please add the option --build-args="--cudaarchs all" to the ./holohub build-container command to include support for AGX Orin's iGPU.

Building Operators, Applications, and Packages

Make sure you have either launched your development container or set up your local environment before attempting to build Holohub components.

This repository provides a convenience holohub script to abstract some of the CMake build process below.

Run the following to list existing components available to build:

./holohub list

Then run the following to build the component of your choice:

# Build using the component name
./holohub build <package|application|operator>
# Ex: ./holohub build endoscopy_tool_tracking

The build artifacts will be created under ./build/<component_name> by default to isolate them from other components which might have different build environment requirements. You can override this behavior and other defaults, see ./holohub build --help for more details.

Running Applications

To list all available applications you can run the following command:

./holohub list

Then you can run the application using the command:

./holohub run <application>
# Ex: ./holohub run endoscopy_tool_tracking

Several applications are implemented in both C++ and Python programming languages. You can request a specific implementation as an argument to the ./holohub run command or omit the argument to use the default language. For instance, the following command will run the Python implementation of the tool tracking endoscopy application:

  ./holohub run endoscopy_tool_tracking --language=python

The run script reads the "run" command from the metadata.json file for a given application and runs from the "workdir" directory. Make sure you build the application (if applicable) before running it.

Cleanup

You can run the command below to reset your build directory:

./holohub clear-cache

In some cases you may also want to clear out datasets downloaded by applications to the data folder:

rm -rf ./data

Note that many applications supply custom container environments with build and runtime dependencies. Failing to clean the build cache between different applications may result in unexpected behavior where build tools or libraries appear to be broken or missing. Clearing the build cache is a good first check to address those issues.

Contributing

The goal of this repository is to allow engineering teams to easily contribute and share new functionalities and to demonstrate applications. Please review the Contributing Guidelines for more information.

Glossary

Many applications use the following keyword definitions in their README descriptions:

<HOLOHUB_SOURCE_DIR> : Path to the source directory
<HOLOHUB_BUILD_DIR> : Path to the build directory
<HOLOSCAN_INSTALL_DIR> : Path to the installation directory of Holoscan SDK
<DATA_DIR> : Path to the top level directory containing the datasets for the reference applications
<MODEL_DIR> : Path to the directory containing the inference model(s)

More Information

Refer to additional documentation:

Contributing Guide
Developer Guide
Release Discussion

You can find additional information on Holoscan SDK at:

Holoscan GitHub organization
Holoscan SDK repository
Holoscan-GPT (requires an OpenAI account)
Holoscan Support Forum

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