Please provide complete information as applicable to your setup.
**• Hardware Platform: Jetson nano
**• DeepStream Version: 5.1 or 6
**• JetPack Version: 4.5.1
**• TensorRT Version: TensorRT 7.1.3
• Issue Type questions / bugs
Hi nvidia community !!,
I have a question concerning a yolov4 model that I trained (custom classes) and I wanted to integrate this model into a Jetson nano using nvidia SDK deepstream_5.1.
It’ works but…
Among the classes that I trained two of them have sometimes overlap boxes (just for the illustration and as example if car and red_car are two different classes, a picture containing a red car in darknet will return 2 boxes with a perfect overlap (same coordinates)). I know it’s weird but anyway darknet deals perfectly with this situation and I recover both classes and even when the boxes overlap perfectly.
To use yolov4 on nano I used Deepstream_5.1 (inside a container) which give really nice result in term of inference. Unfortunately, the engine generator for yolov4 is not yet perfectly incorporate in deepstream and need a lot of prerequisites to work (especially if you use the docker container of deepstream5). Thanks to the very nice repo of Marcos_Luciano (GitHub - marcoslucianops/DeepStream-Yolo: NVIDIA DeepStream SDK 6.1 / 6.0.1 / 6.0 configuration for YOLO models) it is possible to easily convert/parse yolov4 and use it along with deepstream5.1.
But I notice that in the case on my example (two classes with sometimes same boxes coordinates) I didn’t get both classes. It’s seems that it return only one of them (probably the one with the highest probability usually car or rarely red_car but never both).
I suspect somewhere in the code a kind of nms maybe responsible for that?? but I’m not mastering C++ enough to figure it out where could be this.
If anyone faced the same issue or have any idea on that subject. It will be really helpful.
Thx all !