#ifndef __YOLO_HPP__
#define __YOLO_HPP__

#include <future>
#include <memory>
#include <string>
#include <vector>
#include <opencv2/opencv.hpp>

// yolov8 instance segmentation表示不同的模型类型
enum class Type : int {
  V5 = 0,
  X = 1,
  V3 = 2,
  V7 = 3,
  V8 = 5,
  V8Seg = 6  
};

//用于存储实例分割的结果
struct InstanceSegmentMap {
  int width = 0, height = 0;      // width % 8 == 0
  unsigned char *data = nullptr;  // is width * height memory

  InstanceSegmentMap(int width, int height);
  virtual ~InstanceSegmentMap();
};

//表示检测到的物体边界框
struct Box {
  float left, top, right, bottom, confidence;
  int classLabel;
  std::shared_ptr<InstanceSegmentMap> seg;  // valid only in segment task

  Box() = default;
  Box(float left, float top, float right, float bottom, float confidence, int label)
      : left(left),
        top(top),
        right(right),
        bottom(bottom),
        confidence(confidence),
        classLabel(label) {}
};

//表示输入图像。它包含图像数据指针、宽度和高度。
struct Image {
  const void *bgrptr = nullptr;
  int width = 0, height = 0;

  Image() = default;
  Image(const void *bgrptr, int width, int height) : bgrptr(bgrptr), width(width), height(height) {}
};

//存储检测结果的 Box 结构体的容器类型
typedef std::vector<Box> BoxArray;

// [Preprocess]: 0.50736 ms
// [Forward]: 3.96410 ms
// [BoxDecode]: 0.12016 ms
// [SegmentDecode]: 0.15610 ms
//用于执行模型推理并返回检测结果
class Infer {
 public:
  virtual BoxArray forward(const Image &image, void *stream = nullptr) = 0;
  virtual std::vector<BoxArray> forwards(const std::vector<Image> &images,
                                         void *stream = nullptr) = 0;
};

//用于加载指定类型的模型,
std::shared_ptr<Infer> load(const std::string &engine_file, Type type,
                            float confidence_threshold = 0.25f, float nms_threshold = 0.5f);

//返回指定模型类型的字符串表示。
const char *type_name(Type type);
std::tuple<uint8_t, uint8_t, uint8_t> hsv2bgr(float h, float s, float v);
std::tuple<uint8_t, uint8_t, uint8_t> random_color(int id);

//定义了一个 Yolo 类,用于加载 YOLOv8 模型并执行物体检测和实例分割。
class Yolo{
public:
  Yolo(const std::string enginePath) {detector = load(enginePath, Type::V8Seg);};
  static const char *cocoLabels[];
  BoxArray detect(cv::Mat colorMat);
  std::shared_ptr<Infer> detector;
  //yolo-video_demo函数直接返回BoxArray类型（vector<Box>）的objs,可以直接使用obj.left等形式返回物体识别框信息
  //可返回left, top, right, bottom, confidence，box_width，box_height
};




#endif  // __YOLO_HPP__