Hu Chunming / mvpt_dq_ascend_arm

  #ifndef __AI_PLATFORM_HEADER__
  #define __AI_PLATFORM_HEADER__

  
  #ifdef _MSC_VER
  #include <windows.h>
  #else
  
  #include <cstddef>
  
  #endif
  
  #include "sy_common.h"
  #include <map>
  #include <vector>
  #include <string>
  

  #define HUMANREID_FEATURE_SIZE 384
  #define HP_ATTRI_SIZE 16
  

  
  using namespace std;
  
  

  static std::string hair[] = { "长发", "短发", "其他" };
  static std::string hair_color[] = { "黑", "白", "其他" };
  static std::string eye_glass[] = { "未戴眼镜", "戴眼镜" };
  static std::string mask[] = { "未戴口罩", "戴口罩" };
  static std::string up_cloth[] = { "T恤/背心", "衬衫",  "毛衣", "外套", "连衣裙", "其他" };
  static std::string up_cloth_color[] = { "黑", "白", "灰", "红", "蓝", "黄", "绿", "多色", "其他" };
  static std::string clothing_text[] = { "纯色", "碎花", "条纹/格子", "其他" };
  static std::string down_cloth[] = { "长裤", "短裤", "长裙", "短裙", "连衣裙", "其他" };
  static std::string down_cloth_color[] = { "黑", "白", "灰", "红", "蓝", "黄", "绿", "多色", "其他" };
  static std::string bag[] = { "无包", "有包" };
  static std::string sex[] = { "男", "女", "不明" };
  static std::string age[] = { "小孩", "成人", "不明" };
  static std::string viewpoint[] = { "正面","背面", "侧面" };
  static std::string umbrella[] = { "未打伞", "打伞" };
  static std::string hold_baby[] = { "未抱小孩", "抱小孩" };
  static std::string personstate[] = { "行走", "奔跑", "蹲坐", "推车", "其他" };
  

  typedef struct hp_cls_info         //分类结果结构体
  {
      int res_index;                      //分类结果
      float res_prob;                     //分类结构体
      hp_cls_info() : res_index(0), res_prob(0) {};
  } hp_cls_info;
  
  typedef struct VPDInfo
  {
  	int left_;
  	int top_;
  	int width_;
  	int height_;
  
  	int index;		                     //类型
  	float confidence;	                 //置信度
  }VPDInfo;
  
  struct PlateNum
  {
      char character[4];
      float maxprob;
      int index;
  };
  
  struct VehiclePlateResult {
      int left_;
  	int top_;
  	int width_;
  	int height_;
      float detect_score;
  
      PlateNum recg[8];
      float num_score;
      int type;	//车牌类型。只做车牌检测，车牌类型为：0-单层车牌，1-双层车牌;做车牌检测识别，0-单排蓝色 1-单排黄色 2-单排白色 3-单排黑色 4-双排黄色 5-双排白色 6-新能源黄绿色 7-新能源白绿色
  
      int state; //车牌状态：0-无车牌，1-车牌，2-遮挡车牌
      float state_score;//车牌状态置信度
  };
  
  typedef struct ObjectData {
      string task_id;              //该物体属于的任务ID号
      int task_frame_count;     //该物体当前出现的帧号
      int object_id;            //该物体的ID号
      int left;                 //该物体位置的左坐标
      int top;                  //该物体位置的上坐标
      int right;                //该物体位置的右坐标
      int bottom;               //该物体位置的下坐标
      int index;                //该物体所属类别的编号
      double confidence;        //该物体的置信度

      std::string str_ts_ms;   //时间

  
      string ori_pic_path;
      string obj_pic_path;
  

      hp_cls_info hp_cls[HP_ATTRI_SIZE]; 
      float hp_feature[HUMANREID_FEATURE_SIZE];

  
      int vehicle_color_index;
      float vehicle_color_prob;
      vector<VPDInfo> vec_vpd_cls;
      VehiclePlateResult vehicle_plate;
  } ObjectData;
  
  
  
  // TASK初始化参数

  typedef struct task_param {

      string ipc_url;                      //rtsp流地址
      string task_id;                      //外部传入任务id

      int skip_frame{0};

  
      string result_folder_little;         //目标快照抠图保存地址
  	string result_folder;                //目标快照大图保存地址

  } task_param;

  enum ai_log_level {
      AI_LOG_LEVEL_CLOSE = -1,  // 关闭日志
      AI_LOG_LEVEL_TRACE = 0,   // 跟踪变量
      AI_LOG_LEVEL_DEBUG = 1,       // 调试日志
      AI_LOG_LEVEL_INFO = 2,        // 普通日志信息 （如：无关紧要的信息输出）
      AI_LOG_LEVEL_WARNING = 3,     // 警告日志通知，模块一切正常（如：重要流程通知）
      AI_LOG_LEVEL_ERROR = 4,       // 重要日志，如结果和严重错误
  };

  typedef void(*ResultData_CALLBACK)(ObjectData obj);
  

  //VPT初始化参数

  typedef struct tsl_aiplatform_param {
      int gpuid;                                                     //指定显卡id
      string models_dir;              // 模型文件目录
  
      ai_log_level log_level;
      char *log_path;             //日志文件路径
      int log_days;               //日志保存周期
      double log_mem;                //每个日志最大大小

  
      ResultData_CALLBACK result_cbk;

  } tsl_aiplatform_param;

  
  #endif      // __AI_PLATFORM_HEADER__