# Setup with Nvidia-Jetson-Orin

Initial setup and installation of _RapidPoseTriangulation_ on a _Nvidia Jetson_ device. \
Tested with a _Jetson AGX Orin Developer Kit_ module.

<br>

## Base installation

- Install newest software image: \
  (https://developer.nvidia.com/sdk-manager)

- Initialize system: \
  (https://developer.nvidia.com/embedded/learn/get-started-jetson-agx-orin-devkit)

- Install basic tools:

  ```bash
  sudo apt install -y curl nano wget git
  sudo apt install -y terminator
  ```

- Test docker is working:

  ```bash
  sudo docker run --rm hello-world
  ```

- Enable _docker_ without _sudo_: \
  (https://docs.docker.com/engine/install/linux-postinstall/#manage-docker-as-a-non-root-user)

- Enable GPU-access for docker building:

  Run `sudo nano /etc/docker/daemon.json` and add:

  ```json
  {
    "runtimes": {
      "nvidia": {
        "args": [],
        "path": "nvidia-container-runtime"
      }
    },
    "default-runtime": "nvidia"
  }
  ```

  Restart docker: `sudo systemctl restart docker`

- Install _vs-code_: \
  (https://code.visualstudio.com/docs/setup/linux)

- Test docker is working:

  ```bash
  docker run --rm hello-world
  docker run -it --rm --runtime=nvidia --network=host -e DISPLAY=$DISPLAY -v /tmp/.X11-unix/:/tmp/.X11-unix nvcr.io/nvidia/l4t-base:r36.2.0
  docker run -it --rm --runtime=nvidia --network=host dustynv/onnxruntime:1.20-r36.4.0
  ```

- Check _cuda_ access in container:

  ```bash
  python3 -c 'import torch; print(torch.cuda.is_available());'
  ```

- Enable maximum performance mode:

  ```bash
  sudo nvpmodel -m 0
  sudo jetson_clocks
  ```

<br>

## RPT installation

- Build docker container:

  ```bash
  docker build --progress=plain -f extras/jetson/dockerfile -t rapidposetriangulation .
  ./run_container.sh
  ```

- Build _rpt_ package inside container:

  ```bash
  cd /RapidPoseTriangulation/swig/ && make all && cd ../tests/ && python3 test_interface.py && cd ..
  ```

- Test with samples:

  ```bash
  python3 /RapidPoseTriangulation/scripts/test_triangulate.py
  ```

- Evaluate datasets:

  ```bash
  python3 /RapidPoseTriangulation/scripts/test_skelda_dataset.py
  ```

<br>

## ROS interface

- Build docker container:

  ```bash
  docker build --progress=plain -f extras/jetson/dockerfile_ros -t rapidposetriangulation_ros .
  ./run_container.sh
  ```

- Run and test:
  ```bash
  xhost +; docker compose -f extras/jetson/docker-compose.yml up

  docker exec -it ros-test_node-1 bash
  export ROS_DOMAIN_ID=18
  ```