System Requirements

Hardware

Generic

• 1 CPU core per camera. (higher clock CPUs like > 3ghz are generally better)
• 750MB ram per camera
• 7200 RPM Hard Drive or better - Media storage

Optional

• GPU accelerated object detection can be enabled if you have a CUDA compatible graphics card (CUDA enabled GPUS)

Dependencies

Windows

• You may need to install the "Microsoft Visual C++ Redistributable"
  • If the latest redistributable is not installed you can follow the below link to make sure it's installed. Object detection will not work without this Visit to learn more and download Direct download

Linux Generic

• ffmpeg should be installed through package manager.
  • StreamShuttle is tested with ffmpeg >= 6.0
  • if using Ubuntu 22.04 you can utilize the default ffmpeg version, however you will need to disable chunk auth in the device settings. (Edit Device -> Show Advanced Settings -> Disable stream uploader auth)
  • The static builds at https://github.com/BtbN/FFmpeg-Builds also work well.
    • if utilizing the static builds make sure ffmpeg and ffprobe are both added to the PATH.
• ImageMagick should be installed through package manager

Linux with UI

The AppImage should work with most recent versions of common distros.

Ubuntu 22.04

Install libfuse to run StreamShuttle without extracting

sudo add-apt-repository universe
sudo apt install libfuse2

Add appimagelauncher if you want to have a better integration with the OS. This will enable app icons and the start at boot functionality.

sudo add-apt-repository ppa:appimagelauncher-team/stable
sudo apt update
sudo apt install appimagelauncher

Now after downloading StreamShuttle you should be able to just double click the AppImage. You will be prompted to "Run once" or "Integrate and run". Integrate and run will make StreamShuttle available from the AppLauncher.

Linux No UI / (Raspberry PI / ARM)

Manually install nodejs, extract appImage, manually reinstall deps and run services via command line shims instead.

MacOS

Coming soon