Tutorial for People Segmentation with Segformer and TensorRT

Overview

This tutorial walks you through a graph for Image Segmentation for segmenting people in an image using TensorRT.

Tutorial Walkthrough

1. Complete the quickstart up until model preparation step.

2. Activate the Isaac ROS environment:

   isaac-ros activate
   

3. Run the following launch files to start the inferencing:

   ros2 launch isaac_ros_segformer isaac_ros_people_sem_segformer_tensor_rt.launch.py engine_file_path:=${ISAAC_ROS_WS}/isaac_ros_assets/models/peoplesemsegformer/1/model.plan
   

4. Open another terminal and play the rosbag:

   isaac-ros activate
   

   ros2 bag play -l isaac_ros_assets/isaac_ros_segformer/segformer_sample_data --remap image_rect:=image camera_info_rect:=camera_info
   

5. In another terminal, visualize and validate the output of the package by launching rqt_image_view:

   isaac-ros activate
   

   Then launch rqt_image_view:

   ros2 run rqt_image_view rqt_image_view
   

   Then inside the rqt_image_view GUI, change the topic to /segformer/colored_segmentation_mask to view a colorized segmentation mask.

   

   Note

   The raw segmentation is also published to /segformer/raw_segmentation_mask. However, the raw pixels correspond to the class labels and so the output is unsuitable for human visual inspection.