howtoniom.blogg.se - Install ffmpeg python command prompt

And finally, ffmpeg configured and complied with -enable-cuda-nvcc option.

In short, to enable support for GPU-assisted encoding with an NVIDIA GPU for ffmpeg, you need: Please see NVIDIA documentations and ffmpeg wiki page for further information. 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: Some languages might even have libraries of their own to extend FFMPEG natively.

FFMPEG can be used with almost any programming language with a couple of simple tricks. Related: Top 7 Linux GPU Monitoring and Diagnostic Commands Line Tools Result Command line one-liners are great for quick and one off FFMPEG experiences but sooner or later you’re going to want to start building custom applications for efficiency.