Triton deployment and inference

[Morganh]

In TLT 3.0, for post-processing, please refer to https://github.com/NVIDIA-AI-IOT/deepstream_tlt_apps/tree/master/post_processor. For pre-processing, please refer to https://github.com/NVIDIA-AI-IOT/deepstream_tlt_apps/blob/master/configs/frcnn_tlt/pgie_frcnn_tlt_config.txt.

In TLT 2.0, for post-processing, please refer to https://github.com/NVIDIA-AI-IOT/deepstream_tlt_apps/tree/release/tlt2.0.1/nvdsinfer_customparser_frcnn_tlt

Reference topics:
For classification network,

Inferring resnet18 classification etlt model with python

I have an .etlt model and a corresponding .trt classification model which i trained with nvidia tlt, from resnet18 pretrained model. How can i infer it in python? Any suggestion would be appreciated… Thank you.

For detectnet_v2 network,

Run PeopleNet with tensorrt

Hey everyone. After looking into a lot of places, blogs and repos I could manage to run a .engine or .trt file for Detectnet_v2 with preprocessing and proper postprocessing. Here is my working code, hope it helps future persons: import os import time import cv2 import matplotlib.pyplot as plt import numpy as np import pycuda.autoinit import pycuda.driver as cuda import tensorrt as trt from PIL import Image class HostDeviceMem(object): def __init__(self, host_mem, device_mem): se…