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FFmpeg is a set of open source tools for audio and video processing, such as creating, converting/transcoding, and publishing media content.

Audio/Video Codecs:

The FFmpeg docker images are compiled with the following audio and video codecs:

Codec Version Codec Version
fdk-acc 0.1.6 x265 2.9
mp3lame 3.100 vpx 1.7.0
opus 1.2.1 dav1d 0.5.2
ogg 1.3.3 SVT-HEVC v1.5.0
vorbis 1.3.6 SVT-AV1 v0.8.5
x264 stable SVT-VP9* v0.2.1

* SVT-VP9 encoder app only. SVT-VP9 not yet available as a FFmpeg plugin.

Patches:

The FFmpeg builds included the following patches for feature enhancement, better performance or bug fixes:

Patch Description
11625 Enhance 1:N transcoding performance.
H.265 FLV Support H.265 in FLV for RTMP streaming.
ANALYTICS Enables FFmpeg analytics pipeline with the elementary inference features.
SVT-HEVC Enable FFmpeg SVT-HEVC plugin
SVT-AV1 Enable FFmpeg SVT-AV1 plugin

GPU Acceleration:

In GPU images, the FFmpeg docker images are accelerated through VAAPI and/or qsv (Intel® Media SDK). Note that VAAPI or qsv requires special setup for X11 authentication. Please see each platform README for setup details.

Examples:

  • Transcode raw yuv420 content to SVT-HEVC and mp4:
ffmpeg -f rawvideo -vcodec rawvideo -s 320x240 -r 30 -pix_fmt yuv420p -i test.yuv -c:v libsvt_hevc -y test.mp4
  • 1:N Transcoding:
ffmpeg -i input.h264 -vf "scale=1280:720" -pix_fmt nv12 -f null /dev/null -vf "scale=720:480" -pix_fmt nv12 -f null /dev/null -abr_pipeline
  • Encoding/decoding with VAAPI:
ffmpeg -y -vaapi_device /dev/dri/renderD128 -f rawvideo -video_size 320x240 -r 30 -i test.yuv -vf 'format=nv12, hwupload' -c:v h264_vaapi -y test.mp4
ffmpeg -hwaccel vaapi -hwaccel_device /dev/dri/renderD128 -i test.mp4 -f null /dev/null
  • Encoding/decoding with qsv (Intel Media SDK):
ffmpeg -y -init_hw_device qsv=hw -filter_hw_device hw -f rawvideo -pix_fmt yuv420p -s:v 320x240 -i test.yuv -vf hwupload=extra_hw_frames=64,format=qsv -c:v h264_qsv -b:v 5M test.mp4
ffmpeg -hwaccel qsv -c:v h264_qsv -i test.mp4 -f null /dev/null
  • Face detection and emotion identification, save metadata to json format:
ffmpeg -i ~/Videos/xxx.mp4 -vf detect=model=./face-detection-adas-0001/FP32/face-detection-adas-0001.xml:device=CPU, \
classify=model=./emotions_recognition/emotions-recognition-retail-0003.xml:model_proc=emotions-recognition-retail-0003.json:device=CPU, \
metaconvert=converter=json:method=all \
-an -f metapublish -output_format batch -y emotion-meta.json
  • Object Detection:
ffmpeg -i ~/Videos/xxx.mp4 -vf detect=model=./mobilenet-ssd.xml:model_proc=mobilenet-ssd.json:device=CPU -an -f null /dev/null
  • Face detection and reidentification:
ffmpeg -i ~/Videos/xxx.mp4 -vf "detect=model=./face-detection-retail-0004.xml:device=CPU, \
classify=model=./face-reidentification-retail-0095.xml:model_proc=./face-reidentification-retail-0095.json:device=CPU,identify=gallery=./gallery, \
metaconvert=converter=json:method=all" \
-f metapublish -output_format batch -y /tmp/face-identify.json
  • Car attribute recognition:
ffmpeg -i ~/Videos/xxx.mp4 -vf "detect=model=vehicle-detection-adas-0002.xml:model_proc=vehicle-detection-adas-0002.json:device=CPU, \
classify=model=vehicle-attributes-recognition-barrier-0039.xml:model_proc=vehicle-attributes-recognition-barrier-0039.json:device=CPU" -an -f null /dev/null
  • Car-Bike-Person detection:
ffmpeg -i ~/Videos/xxx.mp4 -vf "detect=model=person-vehicle-bike-detection-crossroad-0078.xml:model_proc=person-vehicle-bike-detection-crossroad-0078.json:device=CPU" -an -f null /dev/null
  • GPU decode with VAAPI + detection:
ffmpeg -flags unaligned -hwaccel vaapi -hwaccel_output_format vaapi -hwaccel_device /dev/dri/renderD128 \
-i $STREAM -vf "detect=model=$DETECTION_MODEL:device=$DEVICE" -an -f null - \
  • Face detection, classification with display:
ffplay $SOURCE -sync video -vf \
  "detect=model=$DETECT_MODEL_PATH:device=$DEVICE, \
   classify=model=$CLASS_MODEL_PATH:model_proc=$MODEL_PROC:device=$DEVICE,   \
   classify=model=$CLASS_MODEL_PATH1:model_proc=$MODEL1_PROC:device=$DEVICE, \
   ocv_overlay"

See Also