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QUICKSTART (encoding only)

First download an example video:

mkdir -p samples/videos/ && \
  wget https://service.inet.tu-berlin.de/owncloud/index.php/s/8NA7IFNKN9TgXVA/download -O samples/videos/bigbuckbunny480p24x30s.y4m

Encode the example with fixed segment durations:

sudo docker run --rm -v "$PWD"/samples/videos/:/videos \
                     -v "$PWD"/samples/results/:/results \
                     fginet/docker-video-encoding:latest bigbuckbunny480p24x30s.y4m bigbuckbunny480p24x30s.y4m 41 0 4 0 x264 1.0,2.0,3.0

The command line arguments for variable length bitrate encoding:

<reference_video> <video_id> <crf_value> <min_length> <max_length> 0.0 <codec> <key_frames_t> [<cst_bitrate>]

The command line arguments for fixed length bitrate encoding:

<reference_video> <video_id> <crf_value> <min_length> <max_length> <target_seg_length> <codec> [<cst_bitrate>]

You can find the results in the samples/results folder.

QUICKSTART (with worker and job queue)

Important: Make sure that docker is configured to work without root access.

First make sure you downloaded the video as described about (bigbuckbunny480p24x30s.y4m). Afterwards make a copy of the job template:

cp samples/jobs/00_waiting/bigbuckbunny480p24x30s_var_vbr_job001.txt.tmpl samples/jobs/00_waiting/bigbuckbunny480p24x30s_var_vbr_job001.txt

Start the worker:

python3 worker.py --dry-run --one-job

The following options are used:

  • --dry-run: does not call the container, but prints the docker command.
  • --one-job: quit after processing one job.

You can use different templates:

  • bigbuckbunny480p24x30s_var_vbr_job001.txt.tmpl: Variable Length VBR encoding
  • bigbuckbunny480p24x30s_var_cbr_job002.txt.tmpl: Variable Length CBR encoding
  • bigbuckbunny480p24x30s_fix_vbr_job003.txt.tmpl: Fixed Length VBR encoding
  • bigbuckbunny480p24x30s_fix_cbr_job004.txt.tmpl: Fixed Length CBR encoding

run_workers.sh Script

Use the run_workers.sh script to start a worker on each available core:

cp run_workers_template.sh run_workers.sh

Adapt the paths and parameters in the script and remove the echo from echo screen in the script to activate the workers when you execute the script.

You can stop all running workers after the current job with creating a STOP_WORKERS file in the working directory:

touch STOP_WORKERS

Job/Result Files

Job and result files (video statistics) are managed here. The directory structure can be combine with other usful services allowing a central managing of all workers on a distributed system:

  • WEBDAV
  • SSHFS
  • NFS
  • ...

Video Encoded Files

The docker automatically copies the encoded video files to the SSHFS_DIR or uploads the results via SFTP. Further, you have to specify SFTP or SSHFS_DIR, by comment and uncommenting the metioned lines.

Local Testing

First build the image:

sudo docker build -t fginet/docker-video-encoding:latest .

You can start and enter the build image with:

sudo docker run --rm -it --entrypoint=bash fginet/docker-video-encoding:latest

If you want to test encoding, also add the videos/ and results/ volumes:

sudo docker run --rm -v "$PWD"/samples/videos/:/videos \
                     -v "$PWD"/samples/results/:/results \
                     -it --entrypoint=bash fginet/docker-video-encoding:latest