FWM CLI Packager Guide

PallyCon FWM CLI Packager is a command line interface (CLI) tool for watermark preprocessing and DRM packaging on an encoded video file.

It runs on an on-premise or cloud packaging server built by the content service, and processes the source mp4 video into watermark-preprocessed outputs (0/1 versions, also known as A/B variants).

sequenceDiagram
    participant A as Encoder
    participant B as Packaging server
    participant C as CDN
    A ->> B: Encoded MP4
    Note right of B: FwmPreprocessor
    B -->> B: Watermark Preprocessing
    opt Multi DRM 
    Note right of B: PallyConPackager
    B -->> B: Content packaging and encryption
    end
    Note right of B: ABComposer
    B -->> B: Re-structure filename and directory
    B ->> C: Packaged streams
    Note right of C: DASH / HLS contents<br>(0 and 1 marked)

Modules

You may contact PallyCon team to get the FWM CLI Packager after subscribing to PallyCon Forensic Watermarking plan. It contains the below files.

• FwmPreprocessor: Creates two video files, each marked ‘0’ or ‘1’. For example, when the input content is ‘A.mp4’, it creates ‘A_0.mp4’ and ‘A_1.mp4’. Each of the two generated content can be packaged as DASH / HLS streaming content using PallyCon CLI Packager.

• fmkeyDemo.dat: This is a demo version key file used for watermark preprocessing in a trial account. In addition to the invisible forensic watermark, a visible watermark (`PALLYCON DEMO') will be added in the video preprocessed with the demo key.

• PallyConPackager: CLI-based DRM packager that can produce DRM-encrypted DASH/HLS content with the preprocessed 0/1 version mp4 video.

• ABComposer: Restructures the packaged files for watermark embedding via CDN integration.

• FwmCliPackager.py: A Python script that calls the above modules in a single command.

• Library files: In the lib folder, there are various libraries used in the FwmPreprocessor.

Required environments

You need the following environment to run the FWM CLI Packager.

Hardware

• CPU : Intel CPU
• RAM : 8GB or more
• GPU : NVIDIA graphics card that supports HW video encoding and decoding acceleration
  • NVIDIA Video encoding and decoding GPU support matrix

AWS GPU instance performance

• Geforce GTX1050 (Desktop, Pascal) « P2 (Tesla K80) « P3 (Tesla V100), G3 (Tesla M60)
• When using an AWS EC2 instance as a watermark preprocessing server, we recommend an instance of type P3 or G3 for GPU acceleration.

Software

• Ubuntu server 18.04, 20.04 or CentOS 7
• Intel IPP (Integrated Performance Primitives) 2018: Included in the distribution.
• NVIDIA CUDA Toolkit 9.1 or later (NVIDIA hardware acceleration)
• Dependency libraries
• Python 3.7 or later

Installation guide

NVIDIA CUDA Toolkit 10.0

Pallycon FWM CLI Packager supports NVIDIA H/W encoding/decoding. You can check supported GPUs and codecs here.

It supports CUDA Toolkit 9.1, but 10.0 or higher is recommended. You can also install the latest version if there are no compatibility issues with your other programs. If you need to install other CUDA Toolkit version, please refer latest downlaod or archive.

• Installing on Ubuntu 18.04

  $ distribution=$(. /etc/os-release;echo $ID$VERSION_ID|tr -d '.')
  $ wget https://developer.download.nvidia.com/compute/cuda/repos/${distribution}/x86_64/cuda-repo-${distribution}_10.0.130-1_amd64.deb
  $ sudo dpkg -i cuda-repo-${distribution}_10.0.130-1_amd64.deb
  $ sudo apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/${distribution}/x86_64/7fa2af80.pub
  $ sudo apt-get update
  $ sudo apt-get install -y linux-headers-$(uname -r)
  $ sudo apt-get install -y cuda-10-0
  $ rm cuda-repo-${distribution}_10.0.130-1_amd64.deb
  $ sudo reboot
  

• Installing on CentOS 7

  $ sudo yum install -y https://dl.fedoraproject.org/pub/epel/epel-release-latest-7.noarch.rpm
  $ wget https://developer.download.nvidia.com/compute/cuda/repos/rhel7/x86_64/cuda-repo-rhel7-10.0.130-1.x86_64.rpm
  $ sudo rpm -i cuda-repo-rhel7-10.0.130-1.x86_64.rpm
  $ sudo yum clean all
  $ sudo yum install kernel-devel-$(uname -r) kernel-headers-$(uname -r)
  $ sudo yum install cuda-10-0
  $ rm cuda-repo-rhel7-10.0.130-1.x86_64.rpm
  $ sudo reboot
  

• Installing on AWS Linux2

  • Please refer to this link

• Verification

  $ nvidia-smi
  

• References

  • NVIDIA CUDA Installation guide for Linux
  • CUDA Toolkit 10.0 Download
  • CUDA Toolkit Archive
  • AWS, Installing the NVIDIA Driver on Linux Instances.
  • FFMPEG WITH NVIDIA ACCELERATION ON UBUNTU LINUX

Install Dependencies

• Ubuntu 18.04 version

  $ sudo apt update
  $ sudo apt install -y \
          libva-drm2 \
          libvdpau1 \
          libmediainfo0v5 \
          libpng16-16
  

• Ubuntu 20.04 version

  $ sudo apt update
  $ sudo apt install -y \
          libnuma1 \
          libva-drm2 \
          libvdpau1 \
          libmediainfo0v5 \
          libpng16-16
  

• CentOS 7 version

  $ sudo yum update
  $ sudo yum install -y \
          openssl-devel \
          libpng-devel \
          libmediainfo-devel
  

FWM CLI Packager usage

Execute the FwmCliPackager.py file in the bin folder of the downloaded archive with the following command.

$ python3 FwmCliPackager.py -i INPUT_FILE -o OUTPUT_DIR [optional parameters]

FwmCliPackager parameters

Example commands

Watermark preprocessing + Non-DRM DASH/HLS packaging

The command below produces non-DRM DASH, HLS output with demo (trial) watermark preprocessing applied.

$ python3 FwmCliPackager.py -i ~/fwm/input.mp4 -o ~/fwm/output --demo --dash --hls --disable_encryption

If you are using a commercial forensic watermarking service, enter it without the --demo parameter. (If the commercial seed key fmkey.dat file is stored in the same directory as the executable file)

Watermark preprocessing + DRM packaging

The command below generates DASH and HLS output with commercial version watermark preprocessing and DRM packaging applied. (When manually specifying the commercial key file path)

$ python3 FwmCliPackager.py -i ~/fwm/input.mp4 -o ~/fwm/output --fmkey_file ~/fwm/fmkey.dat --access_key YOUR_ACCESS_KEY --dash --hls --site_id YOUR_SITE_ID --content_id UNIQUE_CONTENT_ID

In the case of ABR (Adaptive Bitrate) content, input original files with different resolutions and bitrates with the -i parameter as shown below.

$ python3 FwmCliPackager.py -i ~/fwm/input_hd.mp4 ~/fwm/input_sd.mp4 -o ~/fwm/output-abr --fmkey_file ~/fwm/fmkey.dat --access_key YOUR_ACCESS_KEY --dash --hls --site_id YOUR_SITE_ID --content_id UNIQUE_CONTENT_ID

Watermark preprocessing only

If you want to package commercially preprocessed A/B version videos using a third-party solution, run the following command. In the resulting directory, two mp4 files with _0 and _1 added after the original file name are created.

$ python3 FwmCliPackager.py -i ~/fwm/input.mp4 -o ~/fwm/output --access_key YOUR_ACCESS_KEY --preprocessing_only

Watermark preprocessing + DRM packaging with external key

When performing commercial watermarking preprocessing and external key input DRM packaging, run the following command.

$ python3 FwmCliPackager.py -i ~/fwm/input.mp4 -o ~/fwm/output --access_key YOUR_ACCESS_KEY --dash --hls --content_id UNIQUE_CONTENT_ID --enable_raw_key_encryption --keys label=:key_id=16BYTE_HEX_STRING:key=16BYTE_HEX_STRING

Packaging option for CDN integration

A/B watermark contents packaged in DASH or HLS format by FWM CLI packager are mixed in real time and delivered to users through watermark embedding integration at CDN edge. Basically, FWM CLI packager adds a separate label to the B version file name among A/B version segment files. (‘Unlabeled A variant’ method) It can be integrated with Akamai CDN or Amazon CloudFront with PallyCon FWM Lambda@Edge Embedder (v2.3 or later) applied.

If you want to integrate with CloudFront to which Lambda@Edge Embedder prior to v2.2.2 has been applied, you must modify the cdnpack_option item defined in the FwmCliPackager class of the FwmCliPackager.py script as follows before executing it. (Creates two sets of content into separate 0/1 directories)

self.cdnpack_option = {"type": "aws"}