Official Docker images for the ZED SDK (https://www.stereolabs.com)
100K+
These images let you use the ZED SDK with docker, even with the ZED camera connected (or an SVO file). https://github.com/stereolabs/zed-docker
Patch versions are now explicitely deployed as well, the current 5.3.1 images are available for all variants, the "5.3" images are pointing to the latest patch, 5.3.1.
All images are based on Nvidia CUDA. You need nvidia-docker to run them, see below.
Please note that these images can't run graphical programs, including the tools. It requires openGL support (see gl-devel tags). All desktop images now include the ZED Python API.
runtime images are the lightest and comes with every dependency installed. It's only meant to run applications linked with the ZED SDK.
devel images contains all development tools to compile application including the cuda toolchain, static libraries, and headers of CUDA and the ZED SDK.
gl-devel images include openGL support to be able to run the tools and sample. It also contains the development tools similarly to devel image. Please note that some images variants are not available since Nvidia didn't release image for recent version of CUDA and Ubuntu https://gitlab.com/nvidia/container-images/cuda/-/issues/147
This the jetsons are usually much more limited in storage, more variants are available to limit the disk space usage. Unlike the desktop images, the OpenGL support is included from the base image provided by Nvidia, and therefore available on all images.
py-devel images contains all development tools to develop applications that uses ZED Python API.
py-runtime images are the lightest and comes with every dependency installed. It's only meant to run applications that uses the ZED Python API.
tools-devel images include the tools and sample and the development tools similarly to devel image. It is the most complete and biggest image.
CUDA 13.0
5.3-runtime-cuda13.0-ubuntu24.04 (5.X/ubuntu/runtime/Dockerfile)5.3-devel-cuda13.0-ubuntu24.04 (5.X/ubuntu/devel/Dockerfile)CUDA 12.8
5.3-runtime-cuda12.8-ubuntu24.04 (5.X/ubuntu/runtime/Dockerfile)5.3-devel-cuda12.8-ubuntu24.04 (5.X/ubuntu/devel/Dockerfile)5.3-gl-devel-cuda12.8-ubuntu24.04 (5.X/ubuntu/gl-devel/Dockerfile)CUDA 13.0
5.3-runtime-cuda13.0-ubuntu22.04 (5.X/ubuntu/runtime/Dockerfile)5.3-devel-cuda13.0-ubuntu22.04 (5.X/ubuntu/devel/Dockerfile)CUDA 12.8
5.3-runtime-cuda12.8-ubuntu22.04 (5.X/ubuntu/runtime/Dockerfile)5.3-devel-cuda12.8-ubuntu22.04 (5.X/ubuntu/devel/Dockerfile)5.3-gl-devel-cuda12.8-ubuntu22.04 (5.X/ubuntu/gl-devel/Dockerfile)CUDA 13.2
5.3-runtime-cuda13.2-ubuntu26.04 (5.X/ubuntu/runtime/Dockerfile)5.3-devel-cuda13.2-ubuntu26.04 (5.X/ubuntu/devel/Dockerfile)L4T 38.4 (JP 7.1)
5.3-devel-jetson-jp7.1.0, 5.3-devel-l4t-r38.4 (5.X/l4t/devel/Dockerfile)5.3-runtime-jetson-jp7.1.0, 5.3-runtime-l4t-r38.4 (5.X/l4t/runtime/Dockerfile)5.3-py-devel-jetson-jp7.1.0, 5.3-py-devel-l4t-r38.4 (5.X/l4t/py-devel/Dockerfile)5.3-py-runtime-jetson-jp7.1.0, 5.3-py-runtime-l4t-r38.4 (5.X/l4t/py-runtime/Dockerfile)5.3-tools-devel-jetson-jp7.1.0, 5.3-tools-devel-l4t-r38.4 (5.X/l4t/tools-devel/Dockerfile)L4T 36.5 (JP 6.2.2)
5.3-devel-jetson-jp6.2.2, 5.3-devel-l4t-r36.5 (5.X/l4t/devel/Dockerfile)5.3-runtime-jetson-jp6.2.2, 5.3-runtime-l4t-r36.5 (5.X/l4t/runtime/Dockerfile)5.3-py-devel-jetson-jp6.2.2, 5.3-py-devel-l4t-r36.5 (5.X/l4t/py-devel/Dockerfile)5.3-py-runtime-jetson-jp6.2.2, 5.3-py-runtime-l4t-r36.5 (5.X/l4t/py-runtime/Dockerfile)5.3-tools-devel-jetson-jp6.2.2, 5.3-tools-devel-l4t-r36.5 (5.X/l4t/tools-devel/Dockerfile)L4T 36.4 (JP 6.1)
5.3-devel-jetson-jp6.1.0, 5.3-devel-l4t-r36.4 (5.X/l4t/devel/Dockerfile)5.3-runtime-jetson-jp6.1.0, 5.3-runtime-l4t-r36.4 (5.X/l4t/runtime/Dockerfile)5.3-py-devel-jetson-jp6.1.0, 5.3-py-devel-l4t-r36.4 (5.X/l4t/py-devel/Dockerfile)5.3-py-runtime-jetson-jp6.1.0, 5.3-py-runtime-l4t-r36.4 (5.X/l4t/py-runtime/Dockerfile)5.3-tools-devel-jetson-jp6.1.0, 5.3-tools-devel-l4t-r36.4 (5.X/l4t/tools-devel/Dockerfile)docker run --gpus all -it --privileged stereolabs/zed:5.3-runtime-cuda12.8-ubuntu24.04
--privileged option is used to pass through all the device to the docker container, it might not be very safe but provides an easy solution to connect the USB3 camera to the container.
To run it, we need to add the right to connect to the X server :
xhost +si:localuser:root
Then to run it :
docker run --gpus all -it --privileged -e DISPLAY -v /tmp/.X11-unix:/tmp/.X11-unix stereolabs/zed:5.3-gl-devel-cuda12.8-ubuntu24.04
Any OpenGL tools are now able to run, for instance :
/usr/local/zed/tools/ZED_Explorer
Since we need CUDA, NVIDIA Container Toolkit must be used (except for compilation only).
Follow the instructions at https://github.com/NVIDIA/nvidia-docker
With the recently added support of nvidia docker, it is now possible to run the ZED SDK inside docker on Jetson. We now provide a compatible image :
docker pull stereolabs/zed:5.3-devel-l4t-r36.5
The image is based on the NVIDIA L4T image.
Content type
Image
Digest
sha256:905f46841…
Size
10.7 GB
Last updated
5 days ago
docker pull stereolabs/zed:5.4-tools-devel-l4t-r39.2