About

This is a minimal example.

Setup

1. git clone this repo
2. run docker build -t ntrl:demo . under the root directory of this repo, once you built the docker image, you don't need to build it again unless you change the dockerfile.
3. run docker run -u $(id -u):$(id -g) --env="DISPLAY" --volume="/tmp/.X11-unix:/tmp/.X11-unix:rw" --volume="/home/n/Eikonal_Planning/ntrl-demo:/workspace" --volume="/usr/lib/x86_64-linux-gnu/:/glu" --volume="/home/n/.local:/.local" --env="QT_X11_NO_MITSHM=1" --gpus all -ti --rm ntrl:demo to start the docker container.
4. run pip install scipy inside the container to install the KD-tree dependency
5. run python dataprocessing/preprocess.py --config configs/gibson.txt to sample training data
6. run python train/train_gib.py to start the training.