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Pose Demo for Jetson/L4T

Logo for Pose Demo for Jetson/L4T
Pose Demo container showcasing pose detection running on Jetson.
Latest Tag
April 1, 2024
Compressed Size
1.31 GB
Multinode Support
Multi-Arch Support
r32.4.2 (Latest) Security Scan Results

Linux / amd64

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Pose Demo Container for Jetson

The pose demo container contains a demo of running pose detection models on Jetson. The container supports running pose detection on a video file input. The model used in this container is a Resnet-18 model which was originally in TensorFlow and was optimized for running on Jetson using TensorRT.

Note that the pose demo currently has TensorRT engine files built for Jetson AGX Xavier and Jetson Xavier NX and hence this demo can be run on Jetson AGX Xavier or Jetson Xavier NX only.

The container requires JetPack 4.4 Developer Preview (L4T R32.4.2)

Running Pose Detection Demo


Ensure these prerequisites are available on your system:

  1. Jetson device running L4T r32.4.2

  2. JetPack 4.4 Developer Preview (DP)

Pulling the container

First, pull the container image:

sudo docker pull

Running the container

To run pose detection on a built-in video, run the following commands:

sudo xhost +si:localuser:root
sudo docker run --runtime nvidia -it --rm --network host -e DISPLAY=$DISPLAY -v /tmp/.X11-unix/:/tmp/.X11-unix python3 /videos/pose_video.mp4 --loop

To run pose detection on a your own video (.h264 format), run the following commands (you would need -v option to mount your video directory)

sudo xhost +si:localuser:root
sudo docker run --runtime nvidia -it --rm --network host -e DISPLAY=$DISPLAY -v /tmp/.X11-unix/:/tmp/.X11-unix -v /my_video_directory/:/userVideos/ python3 /userVideos/my_video_name --loop

Replace my_video_directory with the full path to the directory where you have saved your video and replace my_video_name with the name of your video.

Running the container as part of cloud native demo on Jetson

Cloud native demo on Jetson showcases how Jetson is bringing cloud native methodolgoies like containarizaton to the edge. The demo is built around the example use case of AI applications for service robots and show cases people detection, pose detection, gaze detection and natural language processing all running simultaneously as containers on Jetson.

Please follow for instructions in gitlab on running People detection demo container as part of the cloud native demo.


The pose demo container includes various software packages with their respective licenses included within the container.

Getting Help & Support

If you have any questions or need help, please visit the Jetson Developer Forums.