Please provide complete information as applicable to your setup.
**• Hardware Platform **
• DeepStream Version
**• Issue Type **
questions, new requirements
I am working on a pipeline that involves one primary detector and multiple classification secondary models. I am looking for a way to enhance the speed and performance of the pipeline by running only one of the secondary models based on the result from another secondary model.
Specifically, if one of the secondary models (A) fails to pass the threshold, I would like to disable the other secondary models (B and C ) for inference to reduce processing time. Can you provide guidance on how I can implement this?