#ifndef _RKNN_H_
#define _RKNN_H_

#include "rknn_api.h"
#include <vector>
#include "yolov5.h"


#define MODELDIR "."

#define DEFAULT_CONF_THRESHOLD 0.7
#define HEARTBEAT_SECS 60
extern float conf_threshold;

extern char *CameraID;
extern int TypeID;
extern int UploadPort;


extern int pre_change_frames[OBJ_CLASS_MAX];
// static int last_objects[OBJ_NUMB_MAX_SIZE] = {0};
extern int pre_change_objects[OBJ_CLASS_MAX];

/*
typedef struct _BOX_RECT
{
    int left, right, top, bottom;
} BOX_RECT;

typedef struct __detect_result_t
{
    char name[OBJ_NAME_MAX_SIZE];
    int class_index;
    BOX_RECT box;
    float prop;
} detect_result_t;

typedef struct _detect_result_groupt_t
{
    int id;
    int count;
    detect_result_t results[OBJ_NUMB_MAX_SIZE];
} detect_result_group_t;

typedef struct rknn
{
    rknn_context ctx;
    unsigned char *model;
    int num_input;
    int num_output;

    int model_width;
    int model_height;

    rknn_tensor_attr *out_attrs;

    int (*do_judge)(struct rknn *rk, char *rgb_hwc, int width, int height,
                    int (*callback)(struct rknn *rk, detect_result_group_t *result_group));
    int (*deinit)(struct rknn *rk);
} rknn_t;
*/

extern char *global_model;
extern char *server;

/*
rknn_t *get_rknn();
rknn_t *do_init_model();
rknn_t *reload_rknn(char *model_path);
*/
int process_a_frame(char *buf, int sw, int sh);

/*
int post_process_u8(uint8_t *input0, uint8_t *input1, uint8_t *input2, int model_in_h, int model_in_w,
                    int h_offset, int w_offset, float resize_w_scale, float resize_h_scale, float conf_threshold, float nms_threshold,
                    std::vector<uint8_t> &qnt_zps, std::vector<float> &qnt_scales,
                    detect_result_group_t *group, char *origin_buf);
*/

int print_object_detect_result(rknn_app_context_t* rknn, object_detect_result_list *group, unsigned char *buff);

// #define DUMP_FIRST_FRAME

#endif