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SETUP.md

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Setup

Manual installation

How to setup trt_pose for Jetson Orin Nx.

  1. Check Jetpack version.
sudo apt-cache show nvidia-jetpack
  1. Install corresponding pytorch following this link
sudo apt-get install python3-pip libopenblas-dev
pip install <wheel-name>

or after installing python run:

pip3 install torch torchvision
  1. After installing torch and torchvision, install torch_2_trt
git clone git@github.com:NVIDIA-AI-IOT/torch2trt.git
pip3 install packaging
<set CUDA_HOME var to the location of your cuda installation [export CUDA_HOME=/usr/lib/aarch64-linux-gnu/]>
python3 setup.py install --plugins

** NOT SUCCESSFUL --> FOR NOW **

jetson-containers

Download jetson-containers.

Run exemplary jetson container

jetson-containers run $(autotag l4t-pytorch)

It doesn't assign container name (that's wanted) so it is needed to check name of the container: enter container and then install torch2trt from github repo (as stated above).

After running jetson-containers (remove rm flag in the command), build trt_pose and build torch2trt.

First install torch2trt as follows:

git clone https://github.com/NVIDIA-AI-IOT/torch2trt.git
cd torch2trt
python3 setup.py install 
python3 setup.py install --plugins

After installing torch2trt install trt_pose:

git clone https://github.com/NVIDIA-AI-IOT/trt_pose.git 
python3 setup.py install

Install notebook and tqdm

pip install notebook tqdm pycocotools

Follow README.md from trt_pose to see where to put weights of an NN.

Hacks/Solutions

Problem with import trt_pose.plugins can be solved using following link.

TODO:

  • Explore jetson containers
  • Run contaier from jetson-containers
  • Check trt_pose demo in ROS node
  • Add trt_pose to ROS node
  • Test ROS 2 humble container
  • Add trt_hand_pose
  • Create Dockerfile that's used to setup correct env for HPE on Jetson --> Not possible
  • Create script that set ups fast from jetson-containers base image setup.sh