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Holoscan OpenEmbedded Builder

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OpenEmbedded/Yocto Build Container for NVIDIA Holoscan



Latest Tag



February 1, 2023

Compressed Size

2.85 GB

Multinode Support


Multi-Arch Support


v0.4.0 (Latest) Scan Results

Linux / amd64

OpenEmbedded/Yocto Build Container for NVIDIA Holoscan

This container image contains runtime dependencies, scripts, and the NVIDIA-proprietary binary packages that are required to build an OpenEmbedded BSP image for NVIDIA Holoscan Developer Kits with dGPU support.

The following documentation provides information specific to the usage of the Holoscan Build Container, and may be missing information from the main documentation that may be useful to know when configuring or using the BSP. Please see the main README file for additional documentation.

Note: the main README file can be found at meta-tegra-holoscan/ after following the 1. Setting up the Local Development Environment section, below.

Also note that building a BSP for NVIDIA Holoscan requires a significant amount of resources, and at least 200GB of free disk space is required to build. See the System Requirements section in the main README for more details.

1. Setting up the Local Development Environment

While it would be possible to build an OE image directly from source that is stored within a container, doing so would mean that any additions or modifications to the build recipes would also only live inside the running container and so would be lost whenever the container terminates. Instead, this container operates by initially setting up a local host volume with all of the recipes, dependencies, and initial configuration that is needed for the BSP build such that all of the recipes, configuration, and build cache is stored in persistent storage on the host and thus is not limited to the lifespan of a single container runtime.

In order to perform this initial setup navigate to the directory into which you would like to initialize the development environment and run the following (making sure IMAGE matches the name and tag of this container image):

$ export
$ docker run --rm -v $(pwd):/workspace --network host ${IMAGE} ${IMAGE} $(id -u) $(id -g)

This setup processes initializes the following:

  1. The OE recipes and dependencies in these folders:

  2. A sample build configuration in the build folder.

  3. Wrapper script, which runs a build container and passes the arguments to the script to the container's bitbake command.

  4. A script to flash the device with the built image.

  5. A .buildimage file which contains the name of the container image. This is used by the script and prevents the need to export an IMAGE environment variable anytime a build is performed.

2. Configure the Image

The OE image configuration file is created by the previous step and is written to build/conf/local.conf. This file is based on the default local.conf that is created by the OpenEmbedded environment setup script (oe-init-build-env) and has various NVIDIA configuration defaults and samples added to it. For example, the MACHINE configuration in this file is set to holoscan-devkit and CUDA, TensorRT, Rivermax, and the Holoscan SDK are installed by default. This configuration can be used as-is to build a BSP for the IGX Orin Developer Kit, but it may be neccessary to add components to this configuration to support additional hardware such as AJA video capture cards or other non-standard peripherals like wireless keyboard or mouse drivers. See the Build Configuration section in the main README for more details.

To see the additional configuration that is added to this file relative to the standard OpenEmbedded local.conf, as well as some documentation as to what additional components offered by this meta-tegra-holoscan layer may be enabled, scroll down to the "BEGIN NVIDIA CONFIGURATION" section in this file.

3. Build the Image

Once the image has been configured in the local host development tree, the container image is used again for the actual bitbake build process. This can be done using the build wrapper that is written to the root of the development directory. This script simply runs the bitbake process in the container and passes the arguments to the script to this process. For example, to build a core X11 image, use the following:

$ ./ core-image-x11

Note: If the build fails due to unavailable resource errors, try the build again. Builds are extremely resource-intensive, and having a number of particularly large tasks running in parallel can exceed even 32GB of system memory usage. Repeating the build can often reschedule the tasks so that they can succeed. If errors are still encountered, try lowering the value of BB_NUMBER_THREADS in build/conf/local.conf to reduce the maximum number of tasks that BitBake should run in parallel at any one time.

Using the default configuration, the above script will build the BSP image and write the final output to:


4. Flash the Image

The script can be used to flash the BSP image that is output by the previous step onto the Holoscan Developer Kit hardware. For example, to flash the core-image-x11 image that was produced by the previous step, connect the developer kit to the host via the USB-C debug port, put it into recovery mode, then run:

$ ./ core-image-x11

For instructions on how to put the developer kit into recovery mode, see the developer kit user guide:

Note that flashing the device will require root privileges and so you may be asked for a sudo password by this script.

5. Running the Holoscan SDK Sample Applications

When the holoscan-sdk component is installed, the Holoscan SDK extensions and sample applications will be installed into the image in the /workspace directory. To run a sample application on the flashed device, navigate to this directory and launch the corresponding script. For example, the following runs the endoscopy instrument tracking application using sample recorded video data:

$ cd /workspace
$ ./apps/endoscopy_tool_tracking/cpp/tracking_replayer

Note that the first execution of the samples will rebuild the model engine files and it will take a few minutes before the application fully loads. These engine files are then cached and will significantly reduce launch times for successive executions.