DeepStream tutorial described how to use custom Plugin for new layer with gst-nvinfer.
If I need to use for totally different model like Humanpose https://github.com/ildoonet/tf-pose-estimation.
Humanpose has two parts VGG model and pafprocessing (post processing).
I can run VGG model in TensorRT engine for all different types like FP32/FP16/INT8.
Currently output tensors of TensorRT engine from VGG model is post processed (pafprocessing) in Python.
Since I like to use DeepStream SDK, how can I implement VGG model as primary-gie? I just need Tensor output from output layers.
I can implement post processing in custom plugin referring to SSD or FasterRCNN plugin in TensorRT.