System requirements

Hardware requirements

General

• One CPU core per camera. Higher-clocked CPUs, such as those above 3 GHz, are generally better.
• 750 MB of RAM per camera.
• A 7,200 RPM hard drive or better for media storage.

Optional GPU acceleration

GPU-accelerated object detection can be enabled with a CUDA-compatible GPU.

Software dependencies

Windows

You may need to install the Microsoft Visual C++ Redistributable. Object detection will not work without the latest redistributable.

• Learn more and download
• Direct download

Linux

• Install FFmpeg through your package manager. StreamShuttle is tested with FFmpeg 6.0 or newer.
• On Ubuntu 22.04, you can use the default FFmpeg version, but you must disable chunk authentication under Edit device > Show advanced settings > Disable stream uploader authentication.
• The static FFmpeg builds also work well. When using a static build, add both ffmpeg and ffprobe to your PATH.
• Install ImageMagick through your package manager.

Linux with a UI

The AppImage should work with most recent versions of common Linux distributions.

Ubuntu 22.04

Install libfuse2 to run StreamShuttle without extracting the AppImage:

sudo add-apt-repository universe
sudo apt install libfuse2

Install AppImageLauncher for better integration with the operating system, including application icons and start-at-boot functionality:

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

After downloading StreamShuttle, double-click the AppImage. You will be prompted to Run once or Integrate and run. Choosing Integrate and run makes StreamShuttle available from the application launcher.

Linux without a UI (Raspberry Pi and ARM)

Install Node.js manually, extract the AppImage, reinstall the dependencies, and run the services through command-line shims.

macOS

Coming soon