NVidia Deep Stream - Docker Pipeline Support

Accelerated Computing Intelligent Video Analytics DeepStream SDK
#1

Hello,

I have a AI pipeline which comprises of

  1. ML Model (TFLEARN)
  2. Custom Source Code

I have containerized code with business logic and ML model with Docker and it is working as a pipeline on my Laptop. I would like to know if this Containerized pipeline can be deployed on Deep Stream and can it can work as it is ? If not then please guide me on how I can use my existing Docker container on Deep Stream

I have seen that just ML model can be copied to deep stream and it works. But here in my case I have ML model and associated custom code to do some business logic along with it.

Kindly help.

Amit

• Hardware Platform (Jetson / GPU)
• DeepStream Version
• JetPack Version (valid for Jetson only)
• TensorRT Version
• NVIDIA GPU Driver Version (valid for GPU only)
• Issue Type( questions, new requirements, bugs)
• How to reproduce the issue ? (This is for bugs. Including which sample app is using, the configuration files content, the command line used and other details for reproducing)
• Requirement details( This is for new requirement. Including the module name-for which plugin or for which sample application, the function description)

#3

This seriously depends what the source, ML model and other logic in your application, it’s hard to say whether it can or not without informantion about them.

I think you could take a DS introduction in DeepStream SDK — Accelerating Real Time AI Based Video and Image Analytics - YouTube to understand what DS is and what it can do… it may help you know if it can do what you want

#5

Hi,

Thank you for your reply. I went through that video and its very informative. Can you please share any end to end demonstration of same ? Or any GitHub source ? I can follow and try to implement on similar lines.