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ROS package for pedestrian pedection

This ROS package provides a rosnode, running Python environment with a build-in PyTorch model for Pedestrian Detection. The model is aimed to detect Pedestrians within indoor evrimonent on a data collected with Velodyne VLP16 LiDAR.

The node subscribed to the topic /velodyne_points. Recives /sensor_msgs/PointCloud2 with XYZ and returns /sensor_msgs/PointCloud2 with XYZ and "probability" to the topic /velodyne_points_pedestrians.

Screenshot from 2020-05-02 13-37-17

Usage

To run a rosnode make the following:

  1. Clone this repository to catkin environment:
cd ~/catkin_ws/src
git clone https://github.com/gla-seva/ros_pcd_pedestrian_detector.git
  1. Download pretrained model:
wget -O ros_pcd_pedestrian_detector/scripts/model/UNet_best.pth --no-check-certificate 'https://docs.google.com/uc?export=download&id=1PU6-fHTE9n7xFma6vS2d_w4shnkKkKNi'

  1. Download example .bag from here

  2. Build the package with:

cd ~/catkin_ws/
catkin_make
  1. Run the following nodes (all in separate terminals):

a. Start a roscore

roscore

b. play the bag file:

rosbag play PATH_TO_YOUR_BAG_FILE

c. This nodelet reads raw data from the /velodyne_packets ROS topic, converts to /sensor_msgs/PointCloud2 format, and republishes to /velodyne_points

rosrun nodelet nodelet standalone velodyne_pointcloud/CloudNodelet _model:="VLP16" _calibration:="VLP16db.yaml"

d. Our pedestrian detector:

rosrun ros_pcd_pedestrian_detector pedestrian_detector.py

e. Run RViz to visualise the PointClouds

rosrun rviz rviz -f velodyne

In RViz select Add -> By topic -> /velodyne_points_pedestrians -> PointCloud2