HoangTienDuc

import pycuda.driver as cuda
import pycuda.autoinit
import numpy as np
import tensorrt as trt
import cv2
from hyperpose import Config,Model


TRT_LOGGER = trt.Logger()

HoangTienDuc

import numpy as np
import tritonclient.http as httpclient
import time
import cv2

inputs = []
outputs = []
input_name = "input_1"
output_name = "predictions/Softmax"

HoangTienDuc

import pycuda.driver as cuda
import pycuda.autoinit
import numpy as np
from decoder import CifCafDecoder

import tensorrt as trt
import cv2
import openpifpaf
import torch

HoangTienDuc

Table of contents

• Introduction
• Prerequires
• Installation
• How to use
• Todo

Branch note

HoangTienDuc

# Run server: nvidia-docker run --rm --name trtserver -p 8000:8000 -p 8001:8001  -v `pwd`:/models nvcr.io/nvidia/tritonserver:20.03.1-py3 trtserver --model-store=/models --api-version=2
# Run client: nvidia-docker run -it -v `pwd`:/data --rm --net=host triton:20.03.1


# Run server: nvidia-docker run --rm --name trtserver -p 8000:8000 -p 8001:8001  -v `pwd`:/models nvcr.io/nvidia/tritonserver:20.03.1-py3 trtserver --model-store=/models --api-version=2
# Run client: nvidia-docker run -it -v `pwd`:/data --rm --net=host triton:20.03.1

#!/usr/bin/env python
# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.