containers VS jetson-containers

eclipse-temurin:11 https://hub.docker.com/_/eclipse-temurin

Then you build the container. That will download that container that already has linux with java on it, like this one: https://hub.docker.com/_/eclipse-temurin

You can shrink the docker image greatly by starting with an Alpine based one like this https://hub.docker.com/_/eclipse-temurin

> Just imagine the vast number of poorly cached CI jobs pulling gigabytes from Docker hub on every commit, coupled with naive aproaches to CI/CD when doing microservices, prod/dev/test deployments, etc.

I hit the rate limits that others talk of in the comments, which motivated me to use Nexus for both proxying and storing my own container images.

So far, it's been pretty good, I actually wrote about the process on my blog, "Moving from GitLab Registry to Sonatype Nexus": https://blog.kronis.dev/tutorials/moving-from-gitlab-registr...

Another thing that I tried, however, was to only rely upon Docker Hub for the base images that I want (Ubuntu in my case) and then build everything I need on top of that, doing things like installing Java/Node/Python/Ruby/... manually, adding utilities I want across all of the images etc.

Once again, I wrote about it on my blog, "Using Ubuntu as the base for all of my containers": https://blog.kronis.dev/articles/using-ubuntu-as-the-base-fo...

That approach is absolutely more work, but also is something that's underexplored and works really nicely for me. Now I mostly rely on the OS package manager repositories (or mirrors of those), put less load on Docker Hub, don't risk running into its rate limits and also have common base layers across most of the images that I build, which in practice means less data actually needing to be downloaded to any of the servers where I want to utilize my images.

Of course, the downside is that getting something like PHP running was an absolute pain (tried with Apache, didn't work for some reason, then moved over to Nginx), and I technically miss out on some of the more complex space optimizations because if you look at the Dockerfiles for some of the more popular images, like OpenJDK, you'll occasionally see some interesting approaches, like getting the software package as a bunch of files and "installing" them directly, as opposed to using something like apt/yum: https://github.com/adoptium/containers/blob/08dd7d416cee0fe0...

Then again, personally I'd much prefer to rely on packages that I can get from something like apt directly, even if some of those versions can be a bit older (or add the project's official apt repositories as needed).

The FROM looks incorrect. When i watch the Youtube video it mentions adoptopenjdk which is deprecated (https://hub.docker.com/\_/adoptopenjdk). You now should use https://hub.docker.com/_/eclipse-temurin/.

Eclipse Temurin is maintaining a rich collection of Java images.

Intially only the 17 was the musl-native variant, later added 11 and very recently (6 days ago) for 8 as well: https://github.com/adoptium/containers/issues/72

https://github.com/dusty-nv/jetson-containers This one might be helpful

That's the worst solution because you lose CUDA support, if you don't use the NANO's GPU you can use a Rpi4 instead that has a more powerful CPU. Docker is the solution instead, there are ready images for Jetson: https://github.com/dusty-nv/jetson-containers

Finally, if you don't want the full ros2 desktop on the nano (you may struggle with memory anyway) then jetson containers can run foxy etc with your existing jetpack version. https://github.com/dusty-nv/jetson-containers

I had to modify this dockerfile to get pangolin to work, but now it is the ORB_SLAM2_CODA portion that I cannot figure out.

# Based on https://gitlab.com/nvidia/container-images/l4t-base/-/blob/master/Dockerfile.l4t # https://github.com/dusty-nv/jetson-containers/blob/master/Dockerfile.ros.foxy # https://github.com/codustry/jetson-containers/blob/master/Dockerfile.ros.foxy ARG L4T_MINOR_VERSION=5.0 FROM codustry/ros:foxy-ros-base-l4t-r32.${L4T_MINOR_VERSION} # # ZED Jetson # https://github.com/stereolabs/zed-docker/blob/master/3.X/jetpack_4.X/devel/Dockerfile # ARG ZED_SDK_MAJOR=3 ARG ZED_SDK_MINOR=5 ARG JETPACK_MAJOR=4 ARG JETPACK_MINOR=5 #This environment variable is needed to use the streaming features on Jetson inside a container ENV LOGNAME root ENV DEBIAN_FRONTEND noninteractive RUN apt-get update -y && apt-get install --no-install-recommends lsb-release wget less udev sudo apt-transport-https build-essential cmake openssh-server libv4l-0 libv4l-dev v4l-utils binutils xz-utils bzip2 lbzip2 curl ca-certificates libegl1 python3 -y && \ echo "# R32 (release), REVISION: 5.0" > /etc/nv_tegra_release ; \ wget -q --no-check-certificate -O ZED_SDK_Linux_JP.run https://download.stereolabs.com/zedsdk/${ZED_SDK_MAJOR}.${ZED_SDK_MINOR}/jp${JETPACK_MAJOR}${JETPACK_MINOR}/jetsons && \ chmod +x ZED_SDK_Linux_JP.run ; ./ZED_SDK_Linux_JP.run silent skip_tools && \ rm -rf /usr/local/zed/resources/* \ rm -rf ZED_SDK_Linux_JP.run && \ rm -rf /var/lib/apt/lists/* #This symbolic link is needed to use the streaming features on Jetson inside a container RUN ln -sf /usr/lib/aarch64-linux-gnu/tegra/libv4l2.so.0 /usr/lib/aarch64-linux-gnu/libv4l2.so # # Configure Enviroment for ROS RUN echo 'source /opt/ros/foxy/install/setup.bash' >> ~/.bashrc # RUN echo "source /opt/ros/eloquent/setup.bash" >> ~/.bashrc RUN echo 'source /usr/share/colcon_cd/function/colcon_cd.sh' >> ~/.bashrc # RUN echo "export _colcon_cd_root=~/ros2_install" >> ~/.bashrc # echo $LD_LIBRARY_PATH RUN echo 'export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda-10.2/targets/aarch64-linux/lib/stubs:/opt/ros/foxy/install/lib' >> ~/.bashrc WORKDIR /root/Downloads RUN wget https://developer.nvidia.com/embedded/L4T/r32_Release_v5.0/T186/Tegra186_Linux_R32.5.0_aarch64.tbz2 RUN tar xf Tegra186_Linux_R32.5.0_aarch64.tbz2 RUN cd Linux_for_Tegra && \ sed -i 's/config.tbz2\"/config.tbz2\" --exclude=etc\/hosts --exclude=etc\/hostname/g' apply_binaries.sh && \ sed -i 's/install --owner=root --group=root \"${QEMU_BIN}\" \"${L4T_ROOTFS_DIR}\/usr\/bin\/\"/#install --owner=root --group=root \"${QEMU_BIN}\" \"${L4T_ROOTFS_DIR}\/usr\/bin\/\"/g' nv_tegra/nv-apply-debs.sh && \ sed -i 's/LC_ALL=C chroot . mount -t proc none \/proc/ /g' nv_tegra/nv-apply-debs.sh && \ sed -i 's/umount ${L4T_ROOTFS_DIR}\/proc/ /g' nv_tegra/nv-apply-debs.sh && \ sed -i 's/chroot . \// /g' nv_tegra/nv-apply-debs.sh && \ ./apply_binaries.sh -r / --target-overlay RUN rm -rf Tegra210_Linux_R32.4.4_aarch64.tbz2 && \ rm -rf Linux_for_Tegra && \ echo "/usr/lib/aarch64-linux-gnu/tegra" > /etc/ld.so.conf.d/nvidia-tegra.conf && ldconfig WORKDIR /usr/local/zed ENV CUDA_HOME=/usr/local/cuda WORKDIR /root/ros2_ws/src/ RUN source /opt/ros/foxy/install/setup.bash && cd ../ && colcon build --symlink-install RUN git clone https://github.com/stereolabs/zed-ros2-wrapper.git RUN git clone https://github.com/ros/diagnostics.git && cd diagnostics && git checkout foxy WORKDIR /root/ros2_ws RUN source /opt/ros/foxy/install/setup.bash && source $(pwd)/install/local_setup.bash && rosdep update && \ rosdep install --from-paths src --ignore-src -r --rosdistro ${ROS_DISTRO} -y && \ colcon build --symlink-install --cmake-args " -DCMAKE_BUILD_TYPE=Release" " -DCMAKE_LIBRARY_PATH=/usr/local/cuda/lib64/stubs" " -DCUDA_CUDART_LIBRARY=/usr/local/cuda/lib64/stubs" " -DCMAKE_CXX_FLAGS='-Wl,--allow-shlib-undefined'" && \ echo source $(pwd)/install/local_setup.bash >> ~/.bashrc && \ source ~/.bashrc

Have you tried looking at some jetson nano docker images? https://github.com/dusty-nv/jetson-containers

Yeah, Nvidia has been very slow to release a 20.04 version, but they have provided a lot of Docker containers just for the Jetson for people to use. Here is the Nvidia dev that works on the project.

There are also pip wheels provided. You can easily install them into your system, even without using containers. Also, look at the l4t-ml Dockerfile, which merges some stuff from several containers, using Docker multi-stage builds.