Tutorial for DNN Object Detection with Isaac Sim
================================================

.. figure:: :ir_lfs:`<resources/isaac_ros_docs/concepts/object_detection/detectnet/isaac_sim_detectnet_output.png>`
    :align: center
    :width: 600px

Overview
------------

This tutorial walks you through a pipeline for object(people) detection
using :ir_repo:`DetectNet <isaac_ros_object_detection> <isaac_ros_detectnet>`
consuming images from Isaac Sim.

Tutorial Walkthrough
--------------------

1.  Complete the quickstart :ref:`here <repositories_and_packages/isaac_ros_object_detection/isaac_ros_detectnet/index:quickstart>`.
2.  Launch the Docker container using the ``run_dev.sh`` script:

    .. code:: bash

       cd ${ISAAC_ROS_WS}/src/isaac_ros_common && \
         ./scripts/run_dev.sh

3.  Run the setup script to download the `PeopleNet
    Model <https://catalog.ngc.nvidia.com/orgs/nvidia/teams/tao/models/peoplenet>`__
    from NVIDIA GPU Cloud(NGC) and convert it to a ``.etlt`` file

    .. code:: bash

       cd /workspaces/isaac_ros-dev/src/isaac_ros_object_detection/isaac_ros_detectnet && \
         ./scripts/setup_model.sh --height 720 --width 1280 --config-file resources/isaac_sim_config.pbtxt

4.  Launch the pre-composed pipeline launch file:

    .. code:: bash

       cd /workspaces/isaac_ros-dev && \
         ros2 launch isaac_ros_detectnet isaac_ros_detectnet_isaac_sim.launch.py

5.  Install and launch Isaac Sim following the steps in the :doc:`Isaac ROS Isaac Sim Setup Guide </getting_started/isaac_sim/index>`

6.  Press **Play** to start publishing data from the Isaac Sim.

    .. figure:: :ir_lfs:`<resources/isaac_ros_docs/getting_started/isaac_sim_sample_scene.png>`
        :align: center
        :width: 600px
    
7.  You should see the image from Isaac Sim with the rectangles
    overlaid over detected people in the frame.