yolov5_v6.0.h 2.9 KB
//
// Created by DefTruth on 2021/11/10.
//

#ifndef LITE_AI_TOOLKIT_ORT_CV_YOLOV5_V6_0_H
#define LITE_AI_TOOLKIT_ORT_CV_YOLOV5_V6_0_H

#include "lite/ort/core/ort_core.h"

namespace ortcv
{
  class LITE_EXPORTS YoloV5_V_6_0 : public BasicOrtHandler
  {
  public:
    explicit YoloV5_V_6_0(const std::string &_onnx_path, unsigned int _num_threads = 1) :
        BasicOrtHandler(_onnx_path, _num_threads)
    {};

    ~YoloV5_V_6_0() override = default;

  private:
    // nested classes
    typedef struct
    {
      float r;
      int dw;
      int dh;
      int new_unpad_w;
      int new_unpad_h;
      bool flag;
    } YoloV5ScaleParams;

  private:
    static constexpr const float mean_val = 0.f;
    static constexpr const float scale_val = 1.0 / 255.f;
    const char *class_names[80] = {
        "person", "bicycle", "car", "motorcycle", "airplane", "bus", "train", "truck", "boat", "traffic light",
        "fire hydrant", "stop sign", "parking meter", "bench", "bird", "cat", "dog", "horse", "sheep", "cow",
        "elephant", "bear", "zebra", "giraffe", "backpack", "umbrella", "handbag", "tie", "suitcase", "frisbee",
        "skis", "snowboard", "sports ball", "kite", "baseball bat", "baseball glove", "skateboard", "surfboard",
        "tennis racket", "bottle", "wine glass", "cup", "fork", "knife", "spoon", "bowl", "banana", "apple",
        "sandwich", "orange", "broccoli", "carrot", "hot dog", "pizza", "donut", "cake", "chair", "couch",
        "potted plant", "bed", "dining table", "toilet", "tv", "laptop", "mouse", "remote", "keyboard",
        "cell phone", "microwave", "oven", "toaster", "sink", "refrigerator", "book", "clock", "vase",
        "scissors", "teddy bear", "hair drier", "toothbrush"
    };
    enum NMS
    {
      HARD = 0, BLEND = 1, OFFSET = 2
    };
    static constexpr const unsigned int max_nms = 30000;

  private:
    Ort::Value transform(const cv::Mat &mat_rs) override; // without resize

    void resize_unscale(const cv::Mat &mat,
                        cv::Mat &mat_rs,
                        int target_height,
                        int target_width,
                        YoloV5ScaleParams &scale_params);

    void generate_bboxes(const YoloV5ScaleParams &scale_params,
                         std::vector<types::Boxf> &bbox_collection,
                         std::vector<Ort::Value> &output_tensors,
                         float score_threshold, int img_height,
                         int img_width); // rescale & exclude

    void nms(std::vector<types::Boxf> &input, std::vector<types::Boxf> &output,
             float iou_threshold, unsigned int topk, unsigned int nms_type);

  public:
    void detect(const cv::Mat &mat, std::vector<types::Boxf> &detected_boxes,
                float score_threshold = 0.25f, float iou_threshold = 0.45f,
                unsigned int topk = 100, unsigned int nms_type = NMS::OFFSET);

  };
}

#endif //LITE_AI_TOOLKIT_ORT_CV_YOLOV5_V6_0_H