Hi @mchi, Thanks so much to spend a lot time for guidance me.
1- I investigate the gstnvinfer_meta_utils.cpp, I want to know, Is it possible to change and modify these codes?
2- nvinfer plugin use gstnvinfer_meta_utils.cpp? I want to know If I want to little modify the codes, I have to change only this file code?
3- Is it possible to skip the some classes of object detection? Suppose I want to use PeopleNet and this model has person/face/bag detection and I want to skip the bag class, How do I do? I have to modify gstnvinfer_meta_utils.cpp?
4- Is it possible to add some other task to nvinfer plugin? suppose I want to add face recognition model after peoplenet model, Is it possible? If so, I also need to modify gstnvinfer_meta_utils.cpp?
5- In this picture, they said deep stream is for both developer and enterprises, I want to know how we can the modify and add custom models to deep stream, really it is possible? In opinion, the deep stream is hard code and close-source, I want to know when this SDK is close-source, How we can modify the codes?
Deepstream offers the flexibility for rapid prototyping to full production level solutions and greater flexibility by allowing you to choose your inference path. With native integration to NVIDIA Triton Inference Server, you can deploy models in native frameworks such as PyTorch and TensorFlow for inference or achieve the best possible performance using NVIDIA TensorRT for high throughput inference with options for multi-GPU, multi-stream and batching support.
6- Is it possible to use custom detection or any models in deep stream?
you can deploy models in native frameworks such as PyTorch and TensorFlow for inference
7- It’s adaptive only to Triton or also TensorRT?
best possible performance using NVIDIA TensorRT for high throughput inference
8- When TensorRT gives more performance, Why need to use Teriton?