Repository Summary

Checkout URI https://github.com/aws-robotics/kinesisvideo-encoder-ros2.git
VCS Type git
VCS Version master
Last Updated 2019-09-09
Dev Status DEVELOPED
CI status No Continuous Integration
Released RELEASED
Package Tags No category tags.
Contributing Help Wanted (0)
Good First Issues (0)
Pull Requests to Review (0)

Packages

Name Version
h264_video_encoder 2.0.0

README

h264_video_encoder

Note: this repository is under active development. The package provided here is a release candidate; the API may change without notice and no support is provided for it at the moment.

Overview

This package provides a ROS Node that will encode a stream of images into an H264 video stream.

Keywords: ROS, ROS2, AWS, Kinesis

License

The source code is released under LGPL 2.1. However, this package uses h264_encoder_core which incorporates several different encoding components which may further restrict the license. By default, x264 is used for software encoding, thereby applying GPL to all of h264_video_encoder.

Author: AWS RoboMaker
Affiliation: Amazon Web Services (AWS)
Maintainer: AWS RoboMaker, ros-contributions@amazon.com

Supported ROS Distributions

  • Dashing

Build status

  • Travis CI:
    • "master" branch Build Status
  • ROS build farm:
    • ROS2 Dashing @ u18.04 Bionic Build Status

Installation

Binaries

Not available in apt yet On Ubuntu you can install the latest version of this package using the following command

    sudo apt-get update
    sudo apt-get install -y ros-$ROS_DISTRO-h264-video-encoder

Building from Source

To build from source you'll need to create a new workspace, clone and checkout the latest release branch of this repository, install all the dependencies, and compile. If you need the latest development features you can clone from the master branch instead of the latest release branch. While we guarantee the release branches are stable, the master should be considered to have an unstable build due to ongoing development.

  • Create a ROS workspace and a source directory

    mkdir -p ~/ros-workspace/src
    
  • Clone the package into the source directory

    cd ~/ros-workspace/src
    git clone https://github.com/aws-robotics/kinesisvideo-encoder-ros2.git
    
  • Fetch unreleased dependencies from github

    cd ~/ros-workspace 
    cp src/kinesisvideo-encoder-ros2/.rosinstall.master .rosinstall
    rosws update
    
  • Install dependencies

    cd ~/ros-workspace && sudo apt-get update && rosdep update
    rosdep install --from-paths src --ignore-src -r -y
    
  • Build the packages

    cd ~/ros-workspace && colcon build
    
  • Configure ROS library Path

    source ~/ros-workspace/install/setup.bash
    
  • Build and run the unit tests

    colcon build 
    colcon test && colcon test-results --all
    

Building on Cloud9 - Cross Compilation

  • In RoboMaker's Cloud9, start with an empty workspace and in the Cloud9 console:

    # build docker image cd /opt/robomaker/cross-compilation-dockerfile/ sudo bin/build_image.bash # this step will take a while

    # create workspace mkdir -p ~/environment/robot_ws/src cd ~/environment/robot_ws/src git clone https://github.com/aws-robotics/kinesisvideo-encoder-common.git git clone https://github.com/aws-robotics/kinesisvideo-encoder-ros2.git

    # run docker image cd .. sudo docker run -v $(pwd):/ws -it ros-cross-compile:armhf

  • Now you're inside the cross-compilation docker container

    # build the workspace cd ws apt update rosdep install --from-paths src --ignore-src -r -y # this step will take a while colcon build --build-base armhf_build --install-base armhf_install colcon bundle --build-base armhf_build --install-base armhf_install --bundle-base armhf_bundle --apt-sources-list /opt/cross/apt-sources.yaml # this step will take a while exit

  • Now you're oustide the cross-compilation docker container

    # for more on copying s3 buckets see: https://docs.aws.amazon.com/cli/latest/reference/s3/cp.html aws s3 cp armhf_bundle/output.tar.gz s3:///h264_video_encoder.armhf.tar

Launch Files

A launch file called h264_video_encoder_launch.py is included in this package. The launch file uses the following arguments:

Arg Name Description
node_name (optional) The name the H264 encoder node should be launched with. If not provided, the node name will default to h264_video_encoder
config (optional) A path to a ros2 parameters yaml file. By default uses config/sample_configuration.yaml

Usage

Running the node

To launch the H264 encoder node, you can run the following command:

ros2 launch h264_video_encoder h264_video_encoder_launch.py 

Configuration File and Parameters

An example configuration file called sample_configuration.yaml is provided for running the H264 encoder node on a Raspberry Pi based system. When the parameters are absent, default values are used, thus all parameters are optional. See table below for details.

Parameter Name Description Type
queue_size (optional) The maximum number of incoming and outgoing messages to be queued towards the subscribed and publishing topics. integer
output_width (optional) The desired width (in pixels) of each frame in the encoded video output. integer
output_height (optional) The desired height (in pixels) of each frame in the encoded video output. integer
fps_numerator (optional) The desired frames per second (the numerator portion when expressing FPS as a rational number) for the encoded video output. integer
fps_denominator (optional) The desired frames per second (the denominator portion when expressing FPS as a rational number) for the encoded video output. integer
bitrate (optional) The desired bitrate (in bits per second) of the encoded video output. integer

Node Details

Published Topics

Topic Name Message Type Description
Configurable (default="video/encoded") kinesis_video_msgs/KinesisVideoFrame The node will publish to a topic of a given name. Each message being published contains a chunk of the video stream, usually per video frame.

Subscribed Topics

Topic Name Message Type Description
Configurable (default="/raspicam_node/image") sensor_msgs/Image The node will subscribe to a topic of a given name. The data is expected to be a stream of images from a source (such as a Raspberry Pi camera).

Bugs & Feature Requests

Please contact the team directly if you would like to request a feature.

Please report bugs in Issue Tracker.

CONTRIBUTING

Contributing Guidelines

Thank you for your interest in contributing to our project. Whether it's a bug report, new feature, correction, or additional documentation, we greatly value feedback and contributions from our community.

Please read through this document before submitting any issues or pull requests to ensure we have all the necessary information to effectively respond to your bug report or contribution.

Reporting Bugs/Feature Requests

We welcome you to use the GitHub issue tracker to report bugs or suggest features.

When filing an issue, please check existing open, or recently closed, issues to make sure somebody else hasn't already reported the issue. Please try to include as much information as you can. Details like these are incredibly useful:

  • A reproducible test case or series of steps
  • The version of our code being used
  • Any modifications you've made relevant to the bug
  • Anything unusual about your environment or deployment

Contributing via Pull Requests

Contributions via pull requests are much appreciated. Before sending us a pull request, please ensure that:

  1. You are working against the latest source on the master branch.
  2. You check existing open, and recently merged, pull requests to make sure someone else hasn't addressed the problem already.
  3. You open an issue to discuss any significant work - we would hate for your time to be wasted.

To send us a pull request, please:

  1. Fork the repository.
  2. Modify the source; please focus on the specific change you are contributing. If you also reformat all the code, it will be hard for us to focus on your change.
  3. Ensure local tests pass.
  4. Commit to your fork using clear commit messages.
  5. Send us a pull request, answering any default questions in the pull request interface.
  6. Pay attention to any automated CI failures reported in the pull request, and stay involved in the conversation.

GitHub provides additional document on forking a repository and creating a pull request.

Finding contributions to work on

Looking at the existing issues is a great way to find something to contribute on. As our projects, by default, use the default GitHub issue labels (enhancement/bug/duplicate/help wanted/invalid/question/wontfix), looking at any 'help wanted' issues is a great place to start.

Code of Conduct

This project has adopted the Amazon Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opensource-codeofconduct@amazon.com with any additional questions or comments.

Security issue notifications

If you discover a potential security issue in this project we ask that you notify AWS/Amazon Security via our vulnerability reporting page. Please do not create a public github issue.

Licensing

See the LICENSE file for our project's licensing. We will ask you to confirm the licensing of your contribution.

We may ask you to sign a Contributor License Agreement (CLA) for larger changes.