isaac_ros_h264_decoder

Source code on GitHub.

Quickstart

This quickstart shows an example of how to use the isaac_ros_h264_decoder with a pre-recorded rosbag, which contains compressed H.264 images generated from isaac_ros_h264_encoder with two Argus cameras as the input source. You will be able to visualize the decoded images after the last step.

Set Up Development Environment

  1. Set up your development environment by following the instructions in getting started.

  2. Clone isaac_ros_common under ${ISAAC_ROS_WS}/src.

    cd ${ISAAC_ROS_WS}/src && \
       git clone -b release-3.1 https://github.com/NVIDIA-ISAAC-ROS/isaac_ros_common.git isaac_ros_common
    
  3. (Optional) Install dependencies for any sensors you want to use by following the sensor-specific guides.

    Warning

    We strongly recommend installing all sensor dependencies before starting any quickstarts. Some sensor dependencies require restarting the Isaac ROS Dev container during installation, which will interrupt the quickstart process.

Download Quickstart Assets

  1. Download quickstart data from NGC:

    Make sure required libraries are installed.

    sudo apt-get install -y curl jq tar
    

    Then, run these commands to download the asset from NGC:

    NGC_ORG="nvidia"
    NGC_TEAM="isaac"
    PACKAGE_NAME="isaac_ros_h264_decoder"
    NGC_RESOURCE="isaac_ros_h264_decoder_assets"
    NGC_FILENAME="quickstart.tar.gz"
    MAJOR_VERSION=3
    MINOR_VERSION=1
    VERSION_REQ_URL="https://catalog.ngc.nvidia.com/api/resources/versions?orgName=$NGC_ORG&teamName=$NGC_TEAM&name=$NGC_RESOURCE&isPublic=true&pageNumber=0&pageSize=100&sortOrder=CREATED_DATE_DESC"
    AVAILABLE_VERSIONS=$(curl -s \
        -H "Accept: application/json" "$VERSION_REQ_URL")
    LATEST_VERSION_ID=$(echo $AVAILABLE_VERSIONS | jq -r "
        .recipeVersions[]
        | .versionId as \$v
        | \$v | select(test(\"^\\\\d+\\\\.\\\\d+\\\\.\\\\d+$\"))
        | split(\".\") | {major: .[0]|tonumber, minor: .[1]|tonumber, patch: .[2]|tonumber}
        | select(.major == $MAJOR_VERSION and .minor <= $MINOR_VERSION)
        | \$v
        " | sort -V | tail -n 1
    )
    if [ -z "$LATEST_VERSION_ID" ]; then
        echo "No corresponding version found for Isaac ROS $MAJOR_VERSION.$MINOR_VERSION"
        echo "Found versions:"
        echo $AVAILABLE_VERSIONS | jq -r '.recipeVersions[].versionId'
    else
        mkdir -p ${ISAAC_ROS_WS}/isaac_ros_assets && \
        FILE_REQ_URL="https://api.ngc.nvidia.com/v2/resources/$NGC_ORG/$NGC_TEAM/$NGC_RESOURCE/\
    versions/$LATEST_VERSION_ID/files/$NGC_FILENAME" && \
        curl -LO --request GET "${FILE_REQ_URL}" && \
        tar -xf ${NGC_FILENAME} -C ${ISAAC_ROS_WS}/isaac_ros_assets && \
        rm ${NGC_FILENAME}
    fi
    

Build isaac_ros_h264_decoder

  1. Launch the Docker container using the run_dev.sh script:

    cd ${ISAAC_ROS_WS}/src/isaac_ros_common && \
    ./scripts/run_dev.sh
    
  2. Install the prebuilt Debian package:

    sudo apt-get install -y ros-humble-isaac-ros-h264-decoder
    

Run Launch File

  1. Continuing inside the Docker container, install the following dependencies:

    sudo apt-get install -y ros-humble-isaac-ros-examples
    
  2. Run the following launch file to spin up a demo of this package using the quickstart rosbag:

    ros2 launch isaac_ros_examples isaac_ros_examples.launch.py launch_fragments:=stereo_h264_decoder
    
  3. Open a second terminal inside the Docker container:

    cd ${ISAAC_ROS_WS}/src/isaac_ros_common && \
    ./scripts/run_dev.sh
    
  4. Run the rosbag file to simulate an image stream:

    ros2 bag play -l ${ISAAC_ROS_WS}/isaac_ros_assets/isaac_ros_h264_decoder/quickstart.bag
    

Visualize Results

  1. Open a new terminal inside the Docker container:

    cd ${ISAAC_ROS_WS}/src/isaac_ros_common && \
       ./scripts/run_dev.sh
    
  2. Visualize and validate the output of the package:

    ros2 run image_view image_view --ros-args -r image:=/left/image_uncompressed
    
    ros2 run image_view image_view --ros-args -r image:=/right/image_uncompressed
    

Troubleshooting

Symptom

Launching the decoder node using ros2 launch isaac_ros_h264_decoder isaac_ros_h264_decoder_rosbag.launch.py, produces the below error message:

x86_64 Platform:

[component_container_mt-2] 2023-04-04 22:19:02.609 WARN  /workspaces/isaac_ros-dev/ros_ws/src/isaac_ros_compression/isaac_ros_h264_decoder/gxf/codec/components/decoder.cpp@310: Decoder output is empty, current frame will be dropped

Jetson Platform:

[component_container_mt-2] 2023-04-04 06:39:57.766 WARN  gxf/std/greedy_scheduler.cpp@235: Error while executing entity 20 named 'KIWPUYFVJT_decoder_response': GXF_FAILURE
[component_container_mt-2] [ERROR] (/usr/src/jetson_multimedia_api/samples/common/classes/NvV4l2ElementPlane.cpp:178) <dec0> Capture Plane:Error while DQing buffer: Invalid argument
[component_container_mt-2] 2023-04-04 06:39:57.766 ERROR /workspaces/isaac_ros-dev/ros_ws/src/isaac_ros_compression/isaac_ros_h264_decoder/gxf/codec/components/decoder_request.cpp@530: Failed to dequeue buffer from capture plane
[component_container_mt-2] 2023-04-04 06:39:57.766 ERROR gxf/std/entity_executor.cpp@509: Failed to tick codelet  in entity: KIWPUYFVJT_decoder_response code: GXF_FAILURE
[component_container_mt-2] 2023-04-04 06:39:57.766 ERROR gxf/std/entity_executor.cpp@203: Entity with eid 35 not found!

Solution

You may see these errors when decoder receives P-frames first. Decoder can not decode P-frames until it has received the first I-frame. You can start the decoder before playing the rosbag to avoid these errors.

API

Usage

ros2 launch isaac_ros_h264_decoder isaac_ros_h264_decoder.launch.py

ROS Parameters

ROS Topics Subscribed

ROS Topic

Interface

Description

image_compressed

sensor_msgs/CompressedImage

The H.264 compressed image

ROS Topics Published

ROS Topic

Type

Description

image_uncompressed

sensor_msgs/Image

The uncompressed image with RGB8 encoding.

Output Interpretations

  1. The isaas_ros_h264_decoder package outputs a uncompressed image with the same resolution as the original image. The output image will be in RGB8 format.