Vizon Bundler

Vizon Bundler

Vizon Bundler is an automated event-driven contest-dependent processing pipeline designer and developer. It is a computer vision expert system. One can build vision applications for their targets defining the requirements.

  • Context is the one that defines the operational environment.
  • An event can be defined as an action in the given context
  • It proposes only event-based information extraction and event capsule transmission

Vizon Bundler helps in building the stack to be deployed for the purpose. Once a platform is designed can have the potential to host many contexts and events. Enhances the power of the targeted platform in a multitude.

The typical issues most companies face after they build necessary camera-based systems with necessary hardware accelerators are:

  • Fast adaptability of their hardware for different verticals covering different contexts and events.
  • Hiring and maintaining expensive teams for research and development.
  • Design challenges involved in using complex neural networks.
  • Above all we need very niche expertise in the optimization of the vision system to fit it on target.

The features supported on the Vizon Bundler are:

  • Automated CNN model optimization
  • Automated Model Quantization
  • ALMT – Automated Lean Model Training
  • Resource-aware optimization and quantization
  • On-demand data annotations by crowdsourcing
  • On-demand data collection through crowdsourcing
  • Fully Automated Solution (Lean Model as output)
  • Smaller memory footprint & Power efficient solution
  • Seamless porting of models on to edge devices
  • Minimal loss and guaranteed accuracy
  • Right First Time

Who Needs this? Best fit for Vizon Bundler

Private Companies/Public establishments including government involved in:

  • Building Surveillance solutions
  • Camera companies – Wants to support different applications on their devices
  • Vision analytics companies – Wants to achieve speed, and to fit on target and acceptable accuracy.
  • Embedded vision companies – Looking for Optimal models

Also, teams facing the challenges with following issues needed this solution

  • Not able to fit the model on their targets
  • Not able to control the losses in the quantization
  • Who wants to build hybrid models
  • Multiple inferences from the same input
  • Same inference from multiple inputs
  • Facing challenges adopting models for proper interfaces for HD, FHD, etc.
  • Companies optimizing scheduling the CNN block on their accelerators

Finally, this solution is needed for the teams:

  • Whoever wants to adopt the open-source models for their practical use.