hri_rviz

This package provides a list of rviz2 plugins for human-related data visualisation. It is part of the ROS4HRI ecosystem.

Plugins

Humans

A plugin for visualising 2D information overlayed on a camera stream (ideally, the stream used to detect it). Currently, the plugin can visualise: - Face bounding boxes - Face landmarks - Body bounding boxes - 2D skeleton keypoints

How to use it

1. If not already available, add a Displays panel;
2. press the Add button at the bottom to istantiate a new plugin;
3. select By topic;
4. among the available topics, select the Humans plugin for the camera stream you are interested in;
5. once created the plugin, select which type of information you want to visualise (face bounging boxes, skeleton landmarks, etc.);
6. enjoy!

Skeletons3D

A plugin for visualising the estimated 3D poses of the detected humans.

How to use it

1. If not already available, add a Displays panel;
2. press the Add button at the bottom to istantiate a new plugin;
3. select By display type;
4. select Skeletons3D;
5. enjoy!

TF_HRI

A plugin for visualising the human-related TF frames. These are higly dynamical, appearing and disappearing in a matter of seconds. Using the classic TF plugin would result in a crowded and chaotic frames visualisation. This plugin: - looks over the detected faces and bodies; - only displays the face and bodies TF frames for the currently detected bodies and faces; - readily remove the TF frames for those bodies and faces that are no more tracked, avoiding the disappearing phase observed in the original TF frame for the non-updated frames. It is possible to select which human frames to visualise among: - face frames; - gaze frames; - body frames;

How to use it

1. If not already available, add a Displays panel;
2. press the Add button at the bottom to istantiate a new plugin;
3. select By display type;
4. select TF_HRI;
5. enjoy!

Test

To test the hri_rviz plugins: 1. Download hri_face_detect and hri_fullbody; 2. build them; 3. start an RGB camera stream; 4. start face and body detection: - ros2 launch hri_face_detect face_detect.launch.py filtering_frame:=<camera_frame> rgb_camera:=<rgb_camera_stream_ns> - ros2 launch hri_fullbody hri_fullbody.launch.py rgb_camera:=<rgb_camera_stream_ns> where <rgb_camera_stream_ns> is the RGB camera stream namespace (e.g., /camera/color). This expects the raw RGB images to be published on <rgb_camera_stream_ns>/image_raw. Check the launch files parameters for different options. 5. start the plugins as previously described.

Changelog for package hri_rviz

2.0.0 (2024-05-21)

• re-import CHANGELOG from ROS1
• general cleanup linting code + fixing wrong dependencies in package.xml
• reading body description from the new dedicated topic
• add LICENSE and CONTRIBUTING.md
• using rviz-ogre-vendor instead of native ogre libraries see https://github.com/ros2/rviz/issues/876
• documentation
• fixed icons
• added copyright
• TF (HRI) porting
• Skeletons3D porting
• Humans porting
• Contributors: S