docker container to run tum-vision/dvo_slam (jade-devel) on TUM RGB-D SLAM datasets.
docker build -t dvo_slam_docker:latest .
docker run -ti --rm -v $HOME/code/dvo_slam:/root/ws/src -v $HOME/code/dvo_slam_docker/scripts:/root/scripts -v ~/data/US_CA_MTV_ConsoleCorner1/rgbd/:/dataset dvo_slam_docker:latest /bin/bash scripts/build_and_run.sh
Alternatively:
```shell
docker run -ti --rm -v $HOME/code/dvo_slam:/root/ws/src -v $HOME/code/dvo_slam_docker/scripts:/root/scripts -v $HOME/data/rgbd_dataset_freiburg2_desk:/dataset dvo_slam_docker:latest /bin/bash
docker run -ti --rm -v /path/to/rgbd_dataset_freiburg1_desk:/dataset dvo_slam_docker:latest
modify /path/to/rgbd_dataset_freiburg1_desk
to point to the TUM RGB-D SLAM dataset you want to test. this folder has to contain a file assoc.txt
created with associate.py rgb.txt depth.txt > assoc.txt
.
the estimated trajectory is stored in assoc_opt_traj_final.txt
in the dataset folder.