Hello developers nvidia.
I faced with limited of performance of Deepstream when using back to back detector. The problem is when using more than one engine detector in Deepstream pipeline. Every engines except primary detector engine will need to have more than sequence processing.
Example the primary engine process 32 source and each frame have at least 10 objects then the secondary engine after need processing crop on objects with 32*10 (320) sub-frame. it will be terrible if I want to add the third engines after the second one.
The pre-processing include crop, padding, normalization in gstnvinfer … so I thought this is the main reason make limited of deepstream even though how fast backbone technique engine we are using like resnet, ssd or yolo.
Finally I hope we could have the solutions for this problem like made praralled preprocessing in a batch or something else.
If have any idea to improve performance please discuss or share with us here.