Yolov5 Yolov4 Yolov3 TensorRT Implementation

news: 2021.10.31:yolov5-v6.0 support

INTRODUCTION

The project is the encapsulation of nvidia official yolo-tensorrt implementation. And you must have the trained yolo model(.weights) and .cfg file from the darknet (yolov3 & yolov4). For the yolov5 ,you should prepare the model file (yolov5s.yaml) and the trained weight file (yolov5s.pt) from pytorch.

• [x] yolov5n ,yolov5s , yolov5m , yolov5l , yolov5x ,yolov5-p6 tutorial
• [x] yolov4
• [x] yolov3

Features

• [x] inequal net width and height
• [x] batch inference
• [x] support FP32,FP16,INT8
• [ ] dynamic input size

PLATFORM & BENCHMARK

• [x] windows 10
• [x] ubuntu 18.04
• [x] L4T (Jetson platform)

WRAPPER

Prepare the pretrained .weights and .cfg model.

Detector detector;
Config config;

std::vector<BatchResult> res;
detector.detect(vec_image, res)

Build and use yolo-trt as DLL or SO libraries

windows10

• dependency : TensorRT 7.1.3.4 , cuda 11.0 , cudnn 8.0 , opencv4 , vs2015

• build:

  open MSVC sln/sln.sln file

  • dll project : the trt yolo detector dll
  • demo project : test of the dll

ubuntu & L4T (jetson)

The project generate the libdetector.so lib, and the sample code. If you want to use the libdetector.so lib in your own project,this cmake file perhaps could help you .

git clone https://github.com/enazoe/yolo-tensorrt.git
cd yolo-tensorrt/
mkdir build
cd build/
cmake ..
make
./yolo-trt

API

struct Config
{
    std::string file_model_cfg = "configs/yolov4.cfg";

    std::string file_model_weights = "configs/yolov4.weights";

    float detect_thresh = 0.9;

    ModelType net_type = YOLOV4;

    Precision inference_precison = INT8;

    int gpu_id = 0;

    std::string calibration_image_list_file_txt = "configs/calibration_images.txt";

};

class API Detector
{
public:
    explicit Detector();
    ~Detector();

    void init(const Config &config);

    void detect(const std::vector<cv::Mat> &mat_image,std::vector<BatchResult> &vec_batch_result);

private:
    Detector(const Detector &);
    const Detector &operator =(const Detector &);
    class Impl;
    Impl *_impl;
};

REFERENCE

• https://github.com/wang-xinyu/tensorrtx/tree/master/yolov4
• https://github.com/mj8ac/trt-yolo-app_win64
• https://github.com/NVIDIA-AI-IOT/deepstream_reference_apps

Contact

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