learnopencv/PyTorch-ONNX-TensorRT

How to convert a model from PyTorch to TensorRT and speed up inference

This repository contains code for How to convert a model from PyTorch to TensorRT and speed up inference blogpost.

To run PyTorch part: ```shell script python3 -m pip install -r requirements.txt python3 pytorch_model.py

To run TensorRT part:
1. Download and install NVIDIA CUDA 10.0 or later following by official instruction: [link](https://developer.nvidia.com/cuda-10.0-download-archive)
2. Download and extract CuDNN library for your CUDA version (login required): [link](https://developer.nvidia.com/rdp/cudnn-download)
3. Download and extract NVIDIA TensorRT library for your CUDA version (login required): 
[link](https://developer.nvidia.com/nvidia-tensorrt-6x-download). 
The minimum required version is 6.0.1.5. 
Please follow the [Installation Guide](https://docs.nvidia.com/deeplearning/tensorrt/install-guide/index.html) for your system and don't forget to install Python's part
4. Add the absolute path to CUDA, TensorRT, CuDNN libs to the environment variable ```PATH``` or ```LD_LIBRARY_PATH``` 
5. Install [PyCUDA](https://docs.nvidia.com/deeplearning/tensorrt/install-guide/index.html#installing-pycuda)

```shell script
python3 trt_inference.py

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