Awesome

这个版本已经废弃，最新版本，请移步

• https://github.com/shouxieai/tensorRT_cpp
• 新版本支持了最新版的tensorRT、yolov5，替换了新的解析器，模型编译报错更少

YoloV5 Support

http://zifuture.com:1556/fs/16.std/release_tensorRT_yolov5.zip

TensorRT-Integrate

1. Support pytorch onnx plugin（DCN、HSwish ... etc.）
2. Simpler inference and plugin APIs

Re-implement

CenterNet : ctdet_coco_dla_2x

CenterTrack: coco_tracking

• coco_tracking.onnx download

• nuScenes_3Dtracking.onnx download

DBFace

Use TensorRT-Integrate

install protobuf == 3.11.4 (or >= 3.8.x, But it's more troublesome)

bash scripts/getALL.sh
make run -j32

Inference Code

auto engine = TRTInfer::loadEngine("models/efficientnet-b0.fp32.trtmodel");
float mean[3] = {0.485, 0.456, 0.406};
float std[3] = {0.229, 0.224, 0.225};
Mat image = imread("img.jpg");
auto input = engine->input();

// multi batch sample
input->resize(2);
input->setNormMatGPU(0, image, mean, std);
input->setNormMatGPU(1, image, mean, std);

engine->forward();

// get result and copy to cpu
engine->output(0)->cpu<float>();
engine->tensor("hm")->cpu<float>();

Environment

• tensorRT7.0 or tensorRT6.0
• opencv3.4.6
• cudnn7.6.3
• cuda10.0
• protobuf v3.8.x
• Visual Studio 2017
• lean-windows.zip (include tensorRT、opencv、cudnn、cuda、protobuf)

Plugin

1. Pytorch export ONNX: plugin_onnx_export.py
2. MReLU.cu 、HSwish.cu、DCNv2.cu