RGBD SLAM - Building A ROS 2 Docker Container For Object Detection

Dockerfile

• I installed jupyter notebook so I can experiment with it remotely.

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# -U is to upgrade to the latest version
RUN python3 -m pip install -U jupyter notebook 
# jupyter notebook port
EXPOSE 8888

Docker Runtime Args

• --runtime=nvidia: enable Nvidia Container Runtime, a “runtime” that connects Nvidia GPU with docker. If your laptop doesn’t have an Nvidia GPU, simply remove this arg.
• -p 8888 to expose the Jupyter Notebook Port
• jupyter notebook --ip=0.0.0.0 --no-browser --allow-rootfollows the image name. This is the command to run. without -d, docker will run this process in the foreground, which will terminates the container upon SIGINT (ctrl-C)
• Make sure /dev/shm is shared properly
  • On the same machine, ROS2 uses the directory for messaging
  • But this wouldn’t work -d /dev/shm:/dev/shm
  • use -v instead

Push To Docker Hub

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docker login  #put in docker creds
docker tag <MY_IMAGE>:latest <MY_USERNAME>/<MY_IMAGE>:latest
docker push <MY_USERNAME>/<MY_IMAGE>:latest

• Docker Hub requires images to be pushed to the repo that corresponds to our Docker Hub username. So, we need to tag the image with the proper username.

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