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CaBot People repo

Package Description
cabot_people launch file and script for launching people tracking nodes
track_people_cpp detect and track people (cpp implementation) for improved performance
track_people_msg msgs for track_people packages
track_people_py detect and track people

Test

Preparation

  • run the script to download dependencies
./setup-dependency.sh
  • assume you have docker (Nvidia docker) and docker compose
  • make sure you have a PC with a NVIDIA GPU, or a Jeston (Xavier, Orin, Xavier NX)
  • run one of the following scripts to build image and workspaces
./build-docker.sh -p -i -w              # build image and workspaces for RealSense
./build-docker.sh -p -i -w -c framos    # build image and workspaces for FRAMOS
./build-docker.sh -p -i -w -c all       # build image and workspaces for RealSense and FRAMOS

Bringup Realsense(s), detection, and tracking

  • connect realsense(s) to your PC
  • edit .env file to specify Relasense serial numbers (required if you use multiple)
CABOT_REALSENSE_SERIAL_1=
CABOT_REALSENSE_SERIAL_2=
CABOT_REALSENSE_SERIAL_3=
  • run one of the following script after the build
docker compose -f docker-compose-test-rs3.yaml up rs1 track                   # 1 Realsense on PC
docker compose -f docker-compose-test-rs3.yaml up rs1 rs2 track               # 2 Realsenses on PC
docker compose -f docker-compose-test-rs3.yaml up                             # 3 Realsenses on PC
docker compose -f docker-compose-jetson-test-rs3.yaml up rs1 track            # 1 Realsense on Jetson
docker compose -f docker-compose-jetson-test-rs3.yaml up rs1 rs2 track        # 2 Realsenses on Jetson
docker compose -f docker-compose-jetson-test-rs3.yaml up                      # 3 Realsenses on Jetson

docker compose -f docker-compose-test-rs3-framos.yaml up rs1-framos-camera rs1-framos-detection track-framos                                                # 1 FRAMOS on PC
docker compose -f docker-compose-test-rs3-framos.yaml up rs1-framos-camera rs1-framos-detection rs2-framos-camera rs2-framos-detection track-framos         # 2 FRAMOSes on PC
docker compose -f docker-compose-test-rs3-framos.yaml up                                                                                                    # 3 FRAMOSes on PC
docker compose -f docker-compose-jetson-test-rs3-framos.yaml up rs1-framos-camera rs1-framos-detection track-framos                                         # 1 FRAMOS on Jetson
docker compose -f docker-compose-jetson-test-rs3-framos.yaml up rs1-framos-camera rs1-framos-detection rs2-framos-camera rs2-framos-detection track-framos  # 2 FRAMOSes on Jetson
docker compose -f docker-compose-jetson-test-rs3-framos.yaml up                                                                                             # 3 FRAMOSes on Jetson

Check /people topic

  • check if /people topic is published and recognize someone in front of the camera
  • check if /people topic is published at 10-15 hz per camera, if you have two cameras it publishes at 20-30 hz.
docker exec -it $(docker ps -f name=cabot-people-rs1 -q) bash -c "source install/setup.bash && ros2 topic echo /people"
docker exec -it $(docker ps -f name=cabot-people-rs1 -q) bash -c "source install/setup.bash && ros2 topic hz /people"

License

MIT License