In this guide we aim to document advanced workflows to aid developers in working with HoloHub, and to support advanced project use cases.
- Native Build
- Advanced Container Build Options
- Advanced Container Launch Options
- Advanced Options for Building Applications
- Advanced Options for Running Applications
Refer to the Holoscan SDK README for ways to install Holoscan SDK in local environment: Debian package, Python wheels or from source.
Install the package dependencies for HoloHub on your host system. The easiest way to make sure the minimal package dependencies is to use the ./holohub script from the top level directory.
./holohub setup # sudo privileges may be requiredIf you prefer you can also install the dependencies manually, typically including the following:
- CMake: 3.24.0+
- Python interpreter: 3.9 to 3.12
- Python dev: 3.9 to 3.12 (matching version of the interpreter)
- ffmpeg runtime
- ngc-cli
- wget
- CUDA Toolkit: 12.6
- libcudnn9-cuda-12
- libcudnn9-dev-cuda-12
- libnvinfer-dev
- libnvinfer-plugin-dev
- libnvonnxparsers-dev
Visit the Holoscan SDK User Guide for the latest details on dependency versions and custom installation.
Note: the ./holohub script setup installs the minimal set of dependencies required to run the sample applications. Other applications might require more dependencies. Please refer to the README of each application for more information.
Run the following to view all build options available for the HoloHub container script:
$ ./holohub build-container --helpYou may configure a custom base image for building the HoloHub container. For instance, if you want to use a local Holoscan container as the base image, use the following command:
./holohub build-container --base-img holoscan-sdk-build-x86_64:latest --img holohub:sdk-dev-latestThe command above uses the following arguments:
--base-imgis used to configure the base container image;--imgdefines the fully qualified name of the image output by./holohub.
After ./holohub build-container has completed docker images will list the new image:
user@ubuntu-20-04:/media/data/github/holohub$ docker images
REPOSITORY TAG IMAGE ID CREATED SIZE
holohub sdk-dev-latest cb0231f77856 54 seconds ago 8.22GBBase containers created during the Holoscan SDK build process use the following naming convention by default:
| Base Image Name | Target Architecture | Target IGX Configuration |
|---|---|---|
holoscan-sdk-build-x86_64 |
x86_64 |
N/A |
holoscan-sdk-build-aarch64-dgpu |
aarch64 |
dGPU mode |
holoscan-sdk-build-aarch64-igpu |
aarch64 |
iGPU mode |
Several HoloHub applications use a custom Dockerfile to alter or extend the default HoloHub container. Use the following command to build from a custom Dockerfile:
$ ./holohub build-container --docker-file <path_to_dockerfile> --img holohub-debug:latestWhere:
--docker-fileis the path to the container's Dockerfile;--imgdefines the fully qualified image name.
To print the values for base image, Dockerfile, GPU type, and output image name, use --verbose.
For example, on an x86_64 system with dGPU, the default build command will print the following values when using the --verbose option.
user@ubuntu-20-04:/media/data/github/holohub$ ./holohub build-container --verbose
Build (HOLOHUB_ROOT:/media/data/github/holohub)...
Build (gpu_type_type:dgpu)...
Build (base_img:nvcr.io/nvidia/clara-holoscan/holoscan:v0.6.0-dgpu)...
Build (docker_file_path:/media/data/github/holohub/Dockerfile)...
Build (img:holohub:ngc-v0.6.0-dgpu)...
....Run the command below to view all available launch options in the holohub script:
$ ./holohub run-container --helpTo use a HoloHub container image built with a local Holoscan SDK container:
$ ./holohub run-container --img holohub:local-sdk-latest --local-sdk-root <path_to_holoscan_sdk>where <path_to_holoscan_sdk> is the path to the Holoscan SDK root directory containing the build directory.
Please refer to the Holoscan SDK Developer Guide for more details on how to build the Holoscan SDK from source.
In the container, to verify the build directory (with a python build) is mounted correctly, run the following command:
$ python -c "import holoscan; print(holoscan.__file__)"The output should be something like:
/workspace/holoscan-sdk/build-x86_64/python/lib/holoscan/__init__.pyIf Python supported is not enabled, /workspace/holoscan-sdk can be manually inspected to confirm the mount.
The directory should contain a non-empty build-<arch>-<gpu_type> or install-<arch>-<gpu_type> directory.
To launch custom HoloHub container with fully qualified name, e.g. "holohub:ngc-sdk-sample-app"
$ ./holohub run-container --img holohub:ngc-sdk-sample-app --no-docker-build ./holohub run-container --ssh-x11 ./holohub run-container --nsys-profile./holohub build --helpIf you have an installation of the Holoscan SDK which is not in a standard path, you may want to provide the root directory of your Holoscan SDK installation.
./holohub build --configure-args="-Dholoscan_DIR=/path/to/holoscan/install/lib/cmake/holoscan"By default HoloHub builds all the sample applications that are maintained with the SDK. You can build specific applications by the name of the directory.
./holohub build <application>For example:
./holohub build endoscopy_tool_trackingNote that CMake will build the application in the directory specified. If there are multiple languages, the script will attempt to build all of them.
If you prefer to build applications and operator manually you can follow the steps below.
# Export cuda (in case it's not already in the path)
export PATH=$PATH:/usr/local/cuda/bin
# Configure HoloHub with CMake
cmake -S <path_to_holohub_source> # Source directory
-B build # Build directory
-DPython3_EXECUTABLE=/usr/bin/python3 # Specifies the python executable for CMake to find the correct version
-DHOLOHUB_DATA_DIR=$(pwd)/data # Specifies the data directory
-DAPP_<name_of_the_application>=1 # Specified the application to build
# Build the application(s)
cmake --build buildWhile not all applications requires building HoloHub, the current build system automatically manages dependencies (applications/operators) and also downloads and converts datasets at build time.
You can refer to the README of each application/operator if you prefer to build/run them manually.
The ./holohub script creates a data subdirectory to store the downloaded HoloHub data.
This directory is noted HOLOHUB_DATA_DIR/holohub_data_dir in the documentation, READMEs and metadata files.
./holohub run endoscopy_tool_tracking --language=python --run-args='-r visualizer'For example, to profile endoscopy_tool_tracking using Nsight Systems:
First config the app's replay count to 10 frames:
--- a/applications/endoscopy_tool_tracking/python/endoscopy_tool_tracking.yaml
+++ b/applications/endoscopy_tool_tracking/python/endoscopy_tool_tracking.yaml
@@ -81,7 +81,7 @@ replayer:
frame_rate: 0 # as specified in timestamps
repeat: true # default: false
realtime: true # default: true
- count: 0 # default: 0 (no frame count restriction)
+ count: 10
Then run the app with --nsys-profile option:
./holohub run endoscopy_tool_tracking --language=python --nsys-profileThis will create a Nsight Systems report file in the application working directory. Information on the generated report file is printed on the end of the application log:
Generating '/tmp/nsys-report-bcd8.qdstrm'
[1/1] [========================100%] report8.nsys-rep
Generated:
/workspace/holohub/build/endoscopy_tool_tracking/report8.nsys-rep
This file can be loaded and visualized with the Nsight Systems UI application:
nsys-ui /workspace/holohub/build/endoscopy_tool_tracking/report8.nsys-rep