Now just invoke the service: shell_command. $ ssh passwordless access is working, create the command you want to run in configuration.yaml: ffmpeg_version: ssh -i /config/.ssh/id_rsa -o 'StrictHostKe圜hecking=no' 'ffmpeg -version' Perform an SSH access to your own host to record the data in known_hosts: Configure the add-on, then access the terminal and generate your identification keys: If you have a non-64-bit processor made by AMD, or if you need full support for 32-bit code, use the i386 images instead. I circumvented the problem by running the command via SSH on the host using the “Terminal & SSH” add-on. Choose this to take full advantage of computers based on the AMD64 or EM64T architecture (e.g., Athlon64, Opteron, EM64T Xeon, Core 2). To install a package on Alpine, use the apk command. Remember that the Hassio image for Raspberry Pi 4 is based on Alpine Linux. And finally, ffmpeg configured and complied with -enable-cuda-nvcc option.My solution to run commands installed on the host and that are not present in the Hassio image.In this tutorial, we will learn how to install FFmpeg 4 on Ubuntu 16.04 from a PPA (Personal Package Archive). In short, to enable support for GPU-assisted encoding with an NVIDIA GPU for ffmpeg, you need: If you try to install FFmpeg using the package manager on Ubuntu 16.04 you will notice that the newest version it will give you is 2.8.11, which is a long way off from the latest version. Please see NVIDIA documentations and ffmpeg wiki page for further information. This tutorial will help you to install FFmpeg on Ubuntu 18.04 LTS & 16.04 LTS systems with easy steps. You learned how to install FFmpeg with NVIDIA GPU acceleration hardware support on Debian or Ubuntu Linux to speed up encoding with the ffmpeg command. Make sure you read the following man pages using the man command: Mine is a consumer-grade GPU, but no doubt data center or professional-grade NVIDIA GPU gives even better performance. Time ~/ffmpeg/ffmpeg -hwaccel cuda -y -i /tmp/input.mkv /tmp/out.mp4 Time command outputs with CPU used: realđm40.678sĪlso note down the speed: frame= 7320 fps= 73 q=-1.0 Lsize= 58306kB time=00:02:02.03 bitrate=3914.0kbits/s speed=1.22xĪnd now same file with NVIDIA GPU acceleration (note the path, I am calling the compiled version): Time /bin/ffmpeg -y -i /tmp/input.mkv /tmp/out.mp4 In this example, I am converting input.mkv to out.mp4 as follows without using GPU acceleration: Related: Top 7 Linux GPU Monitoring and Diagnostic Commands Line Tools Result ffmpeg Description: Tools for transcoding, streaming and playing of multimedia files.

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