Dockerfile.desktop
can be used for easy installation. This chapter provides instructions on building and running examples with PangolinViewer support using Docker.
The instructions are tested on Ubuntu 20.04. Docker for Mac are NOT supported due to OpenGL forwarding. Please install the dependencies manually <chapter-installation>
or use the docker images for SocketViewer <section-instructions-for-socketviewer>
.
Execute the following commands:
git clone --recursive https://github.com/stella-cv/stella_vslam.git
cd stella_vslam
docker build -t stella_vslam-desktop -f Dockerfile.desktop .
You can accelerate the build of the docker image with --build-arg NUM_THREADS=<number of parallel builds>
option. For example:
# building the docker image with four threads
docker build -t stella_vslam-desktop -f Dockerfile.desktop . --build-arg NUM_THREADS=`expr $(nproc) - 1`
In order to enable X11 forwarding, supplemental options (-e DISPLAY=$DISPLAY
and -v /tmp/.X11-unix/:/tmp/.X11-unix:ro
) are needed for docker run
.
# before launching the container, allow display access from local users
xhost +local:
# launch the container
docker run -it --rm --privileged -e DISPLAY=$DISPLAY -v /tmp/.X11-unix/:/tmp/.X11-unix:ro stella_vslam-desktop
After launching the container, the shell interface will be launched in the docker container.
root@ddad048b5fff:/stella_vslam/build# ls
lib run_image_slam run_video_slam
run_euroc_slam run_kitti_slam run_tum_slam
See Tutorial <chapter-simple-tutorial>
to run SLAM examples in the container.
If you need to access to any files and directories on a host machine from the container, bind directories <section-directory-binding>
between the host and the container.
Dockerfile.socket
and viewer/Dockerfile
can be used for easy installation. This chapter provides instructions on building and running examples with SocketViewer support using Docker.
Docker Image of stella_vslam `
Execute the following commands:
cd /path/to/stella_vslam
docker build -t stella_vslam-socket -f Dockerfile.socket .
You can accelerate the build of the docker image with --build-arg NUM_THREADS=<number of parallel builds>
option. For example:
# building the docker image with four threads
docker build -t stella_vslam-socket -f Dockerfile.socket . --build-arg NUM_THREADS=`expr $(nproc) - 1`
Execute the following commands:
cd /path/to/stella_vslam
cd viewer
docker build -t stella_vslam-viewer .
Launch the server container and access to it with the web browser in advance. Please specify --net=host
in order to share the network with the host machine.
$ docker run --rm -it --name stella_vslam-viewer --net=host stella_vslam-viewer
WebSocket: listening on *:3000
HTTP server: listening on *:3001
After launching, access to http://localhost:3001/
with the web browser.
Next, launch the container of stella_vslam. The shell interface will be launched in the docker container.
$ docker run --rm -it --name stella_vslam-socket --net=host stella_vslam-socket
root@hostname:/stella_vslam/build#
See Tutorial <chapter-simple-tutorial>
to run SLAM examples in the container.
If you need to access to any files and directories on a host machine from the container, bind directories <section-directory-binding>
between the host and the container.
Launch the server container and access to it with the web browser in advance. Please specify -p 3001:3001
for port-forwarding.
$ docker run --rm -it --name stella_vslam-viewer -p 3001:3001 stella_vslam-viewer
WebSocket: listening on *:3000
HTTP server: listening on *:3001
After launching, access to http://localhost:3001/
with the web browser.
Then, inspect the container's IP address and append the SocketPublisher.server_uri
entry to the YAML config file of stella_vslam.
# inspect the server's IP address
$ docker inspect stella_vslam-viewer | grep -m 1 \"IPAddress\" | sed 's/ //g' | sed 's/,//g'
"IPAddress": "172.17.0.2"
# config file of stella_vslam
...
#============================#
# SocketPublisher Parameters #
#============================#
# append this entry
SocketPublisher.server_uri: "http://172.17.0.2:3000"
Next, launch the container of stella_vslam. The shell interface will be launched in the docker container.
$ docker run --rm -it --name stella_vslam-socket stella_vslam-socket
root@hostname:/stella_vslam/build#
Tutorial <chapter-simple-tutorial>
to run SLAM examples in the container.Please don't forget to append
SocketPublisher.server_uri
entry to the config.yaml
if you use the downloaded datasets in the tutorial.If you need to access to any files and directories on a host machine from the container, bind directories <section-directory-binding>
between the host and the container.
If you need to access to any files and directories on a host machine from the container, bind directories between the host and the container using --volume
or --mount
option. (See the docker documentataion.)
For example:
# launch a container of stella_vslam-desktop with --volume option
$ docker run -it --rm --runtime=nvidia -e DISPLAY=$DISPLAY -v /tmp/.X11-unix/:/tmp/.X11-unix:ro \
--volume /path/to/dataset/dir/:/dataset:ro \
--volume /path/to/vocab/dir:/vocab:ro \
stella_vslam-desktop
# dataset/ and vocab/ are found at the root directory in the container
root@0c0c9f115d74:/# ls /
... dataset/ vocab/ ...
# launch a container of stella_vslam-socket with --volume option
$ docker run --rm -it --name stella_vslam-socket --net=host \
--volume /path/to/dataset/dir/:/dataset:ro \
--volume /path/to/vocab/dir:/vocab:ro \
stella_vslam-socket
# dataset/ and vocab/ are found at the root directory in the container
root@0c0c9f115d74:/# ls /
... dataset/ vocab/ ...