#pragma once #ifdef _MSC_VER #include #else #include #endif #include "sy_common.h" #define DETECTTYPE 9 //二次属性分析结果结构体 #ifndef __CLASSIFY_OBJ_RESULT__ #define __CLASSIFY_OBJ_RESULT__ typedef struct classify_obj_res //分类结果结构体 { int res_index; //分类结果 float res_prob; //分类结构体 classify_obj_res() : res_index(0), res_prob(0) {}; } classify_obj_res; #endif //行人二次属性分析结构 + 特征结果 #ifndef __HP_OBJ_RESULT__ #define __HP_OBJ_RESULT__ const int HP_FIR_INDEX_SIZE = 16; const int HF_FEA_SIZE = 128; typedef struct hp_res { classify_obj_res res_objs[HP_FIR_INDEX_SIZE]{}; //分类结果 } hp_res; #ifndef __INT8__ #define __INT8__ typedef unsigned char int8; #endif typedef struct hp_result { hp_res res_objs{}; //分类结果 int8 feature[HF_FEA_SIZE]{}; //特征 } hp_result; #endif //人骑车二次属性分析结构 + 特征结果 #ifndef __HCP_OBJ_RESULT__ #define __HCP_OBJ_RESULT__ const int HCP_FIR_INDEX_SIZE = 14; const int HCF_FEA_SIZE = 128; typedef struct hcp_res { classify_obj_res res_objs[HCP_FIR_INDEX_SIZE]{}; //分类结果 } hcp_res; typedef struct hcp_result //人骑车二次属性分析以及特征结果 { hcp_res res_objs{}; //分类结果 int8 feature[HCF_FEA_SIZE]{}; //特征 } hcp_result; #endif #define VEHICLE_FEA_SIZE 128 #define PLATENUM 8 //车牌号码位数 #define MAX_PALTE_COUNT 10 //每张图片中最多检测出10个车牌 #define SINGLETYPE_BLUE 0 //单排蓝色 #define SINGLETYPE_YELLOW 1 //单排黄色 #define SINGLETYPE_WHITE 2 //单排白色 #define SINGLETYPE_BLACK 3 //单排黑色 #define DOUBLETYPE_YELLOW 4 //双排黄色 #define DOUBLETYPE_WHITE 5 //双排白色 #define NEWENERGYTYPE_YELLOWGREEN 6 //新能源黄绿色 #define NEWENERGYTYPE_WHITEGRA 7 //新能源白绿色 //车牌号码 #ifndef VPLATENUM_RESULT_ #define VPLATENUM_RESULT_ typedef struct vplate_num { char character[4]; float maxprob; }vplate_num; #endif #ifndef VP_RESULT_ #define VP_RESULT_ typedef struct vplate_result { sy_rect rect; float detect_score; vplate_num recg[PLATENUM]; float num_score; int type; //车牌类型 }vplate_result; #endif #ifndef VR_RESULT_ #define VR_RESULT_ typedef struct vr_result //结果 { char vehicle_brand[260]; //车辆品牌 char vehicle_subbrand[260]; //车辆子品牌 char vehicle_issue_year[260]; //车辆年款 char vehicle_type[260]; //车辆类型 char freight_ton[260]; //货车吨级 float name_score; //识别置信度 }vr_result; #endif #ifndef VC_RESULT_ #define VC_RESULT_ typedef struct vc_result { int res_index; //车颜色结果index float res_prob; //识别置信度 vc_result() : res_index(0), res_prob(0) {}; }vc_result; #endif //VEHICLE #ifndef __VEHICLE_OBJ_RESULT__ #define __VEHICLE_OBJ_RESULT__ typedef struct vehicle_result //车二次属性分析结果 { vr_result vr_res; //车型识别结果 vc_result vc_res; //车颜色识别结果 vplate_result vp_res; //车牌检测结果 int8 feature[VEHICLE_FEA_SIZE]{}; //车辆特征 } vehicle_result; #endif //返回的检测物体快照结果 #ifndef __VIDEO_OBJECT_SNAPSHOT__ #define __VIDEO_OBJECT_SNAPSHOT__ typedef struct video_object_snapshot { int task_id; //该物体属于的任务ID号 int object_id; //该物体的ID号 char video_image_path[256]; //该物体快照的视频截图保存路径 char snapshot_image_path[256]; //该物体快照抠图保存路径 int object_type_index; //该物体所属类别的索引 char obj_type[64]; //该物体属于的类别 double progress; //该路视频的检测进度 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 double confidence; //置信度 void* analysisRes; //二次属性分析结果 } video_object_snapshot; #endif //返回的检测物体结果信息 #ifndef __VIDEO_OBJECT_INFO__ #define __VIDEO_OBJECT_INFO__ typedef struct video_object_info { int 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 } video_object_info; #endif //回调函数，通知处理结束的视频,返回任务ID号 typedef void(*VIDEO_OBJECT_INFO_CALLBACK)(void * handle, video_object_info *obj_info); //回调函数，返回检测物体的快照信息 typedef void(*VIDEO_OBJECT_SNAPSHOT_CALLBACK)(void * handle, video_object_snapshot *snapshot_info); //回调函数，返回实时查看时视频的图像 typedef void(*VIDEO_REALTIME_CALLBACK)(void * handle, unsigned char *img_data, int img_height, int img_width); //回调函数，通知处理结束的视频,返回任务ID号 typedef void(*VIDEO_FINISH_CALLBACK)(void * handle, const int task_id); //TASK初始化参数 #ifndef __TASK_PARAM__ #define __TASK_PARAM__ typedef struct task_param { const char* video_filename; const char* result_folder_little; const char* result_folder; sy_rect minBoxsize[DETECTTYPE]; //自定义的minBoxsize大小 VIDEO_OBJECT_SNAPSHOT_CALLBACK obj_snapshot_callback_func; VIDEO_REALTIME_CALLBACK rt_view_callback_func; }task_param; #endif //VPT初始化参数 #ifndef __MVPT_PARAM__ #define __MVPT_PARAM__ typedef struct mvpt_param { int gpuid; //指定显卡id char* vrdbpath; //指定车行识别的车型数据库的路径 //算法配置参数 sy_command hp_analysis_config; //是否开启行人结构化识别 sy_command hcp_analysis_config; //是否开启人骑车结构化识别 sy_command vehicle_analysis_config; //是否开启车型识别 sy_command hf_recg_config; //是否开启行人特征识别 sy_command hcf_recg_config; //是否开启人骑车特征识别 sy_command vcf_recg_config; //是否开启车辆特征识别 VIDEO_OBJECT_INFO_CALLBACK task_obj_info_callback_func; //目标检测结果实时返回回调函数 VIDEO_FINISH_CALLBACK task_finish_callbackfunc; //任务分析结束结果回调函数 }mvpt_param; #endif #ifndef _MSC_VER #include #define MACRO_COUNT_TIME_START struct timeval macro_tv_start;\ struct timeval macro_tv_end;\ gettimeofday(¯o_tv_start,NULL); #define MACRO_COUNT_TIME_END(___total_count___) gettimeofday(¯o_tv_end,NULL);\ if(___total_count___<=0)\ printf("time cost: %.2f ms \n", ( (double)(macro_tv_end.tv_sec-macro_tv_start.tv_sec)*1000000+(double)(macro_tv_end.tv_usec-macro_tv_start.tv_usec) )/1000);\ else\ printf("time cost: %.2f ms \n", ( (double)(macro_tv_end.tv_sec-macro_tv_start.tv_sec)*1000000+(double)(macro_tv_end.tv_usec-macro_tv_start.tv_usec) )/1000/___total_count___); #endif