Overview / Usage

The video curation sample (concept in active development) implements libraries of video files- content analysis, database ingestion, content search, and visualization.

Methodology / Approach

This sample implements libraries of video files content analysis, database ingestion, content search and visualization:

• Ingest: Analyze video content and ingest the data into the VDMS.
• VDMS: Store metadata efficiently in a graph-based database.
• Visualization: Visualize content search based on video metadata.

This is a concept sample in active development.

The sample is powered by the following Open Visual Cloud software stacks:

• Media Analytics:

  • The GStreamer-based media analytics stack is used for object, face and emotion detection. The software stack is optimized for Intel® Xeon® Scalable Processors.

• NGINX Web Service:

  • The NGINX/FFmpeg-based web serving stack is used to store and segment video content and serve web services. The software stack is optimized for Intel Xeon Scalable Processors.

• Time Zone: Check that the timezone setting of your host machine is correctly configured. Timezone is used during build. If you plan to run the sample on a cluster of machines managed by Docker Swarm or Kubernetes, please make sure to synchronize time among the manager/master node and worker nodes.

• Build Tools: Install cmake and m4 if they are not available on your system.

• Docker Engine:

  • Install docker engine.
  • Install docker compose, if you plan to deploy through docker compose. Version 1.20+ is required.
  • Setup docker swarm, if you plan to deploy through docker swarm. See Docker Swarm Setup for additional setup details.
  • Setup Kubernetes, if you plan to deploy through Kubernetes. See Kubernetes Setup for additional setup details.
  • Setup docker proxy as follows if you are behind a firewall:

  sudo mkdir -p /etc/systemd/system/docker.service.d
  printf "[Service]\nEnvironment="HTTPS_PROXY=$https_proxy" "NO_PROXY=$no_proxy"\n" | sudo tee /etc/systemd/system/docker.service.d/proxy.conf
  sudo systemctl daemon-reload
  sudo systemctl restart docker

mkdir build    

cd build
cmake ..
make

See also: Customize Build Process.

Use the following commands to start/stop services via docker-compose:

make start\_docker\_compose      

make stop_docker_compose

Use the following commands to start/stop services via docker swarm:

make update # optional for private registry

make start_docker_swarm
make stop_docker_swarm

See also: Docker Swarm Setup.

Use the following commands to start/stop Kubernetes services:

make update # optional for private registry

make start_kubernetes
make stop_kubernetes

See also: Kubernetes Setup.

Launch your browser and browse to https://<hostname>. The sample UI is similar to the followin

• For Kubernetes/Docker Swarm, <hostname> is the hostname of the manager/master node.
• If you see a browser warning of self-signed certificate, please accept it to proceed to the sample UI.

Technologies Used

Open Visual Cloud

The sample is powered by the following Open Visual Cloud software stacks:

• Media Analytics:

  • The GStreamer-based media analytics stack is used for object, face and emotion detection. The software stack is optimized for Intel® Xeon® Scalable Processors.

• NGINX Web Service:

  • The NGINX/FFmpeg-based web serving stack is used to store and segment video content and serve web services. The software stack is optimized for Intel Xeon Scalable Processors.

Repository

https://github.com/OpenVisualCloud/Video-Curation-Sample