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ffmpeg's Introduction

NVIDIA accelerated ffmpeg

Build Status Dockerhub link Singularity hub link

Features

NVENCODE (nvenc) and NVDECODE (formerly CUVID) are packaged in the NVIDIA Video Codec SDK.

Hardware Accelerated Encoders:

List options of an encoder using ffmpeg -h encoder=XXXX

  • h264_nvenc, nvenc, nvenc_h264
  • nvenc_hevc, hevc_nvenc

Hardware Accelerated Decoders:

List options of a decoder using ffmpeg -h decoder=XXXX

  • h264_cuvid
  • hevc_cuvid
  • mjpeg_cuvid
  • mpeg1_cuvid
  • mpeg2_cuvid
  • mpeg4_cuvid
  • vc1_cuvid
  • vp8_cuvid
  • vp9_cuvid

Hardware Accelerated Filters:

List options of a filter using ffmpeg -h filter=XXXX

  • hwupload_cuda
  • scale_cuda
  • scale_npp
  • thumnail_cuda

Usage

Run the container mounting the current directory to /workspace processing input.mp4 to output.mp4 without any hardware acceleration

$ docker run --rm -it --runtime=nvidia \
    --volume $PWD:/workspace \
    willprice/nvidia-ffmpeg -i input.mp4 output.avi
$ docker run --rm -it --runtime=nvidia \
    --volume $PWD:/workspace \
    willprice/nvidia-ffmpeg \
      -hwaccel_device 0 \
      -hwaccel cuvid \
      -c:v h264_cuvid \
      -i input.mp4 \
      -c:v hevc_nvenc
      out.mkv

Get a shell prompt inside the container, useful for debugging:

$ docker run --rm -it --runtime=nvidia \
    --volume $PWD:/workspace \
    --entrypoint bash
    willprice/nvidia-ffmpeg

Build

The docker image is a multistage build. The initial stage, the build stage, builds a statically linked ffmpeg binary that is then copied over into the runtime image. By statically linking we minimize the number of external dependencies and shrink the runtime image.

Resources

ffmpeg's People

Contributors

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Watchers

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