behavior_analysis_data 行为分析与人车物分离
功能介绍
行为分析与人车物分离业务:对人车物行为进行分析生成相应数据的智能场景。
行为分析与人车物分离业务消息体的message_type值为behavior_analysis_data 。
目前行业视频管理服务会处理以下场景:
itgt_type/target_type枚举值:
- 21 行为分析抓图(摄像机SDC/NVR800开启行为分析功能,目标进入区域且触发入侵、越线、徘徊、遗留、移走、区域进入、区域离开、快速移动等告警,则进行抓拍并分析目标信息,如:目标类型、目标状态、目标速度等)
|
字段名 |
类型 |
说明 |
|---|---|---|
|
device_id |
String |
设备ID,正常情况下不为空,必传 |
|
channel_id |
String |
通道ID,正常情况下不为空,必传 |
|
data_id |
String |
数据ID:正常情况下不为空,必传。可用于查询智能图片数据,参考链接:智能图片下载 |
|
report_time |
String |
上报时间:示例:2021-03-15T16:43:00+08:00 |
|
data |
Data object |
业务信息 |
|
字段名 |
类型 |
说明 |
|---|---|---|
|
common |
Common object |
通用数据定义 |
|
rule |
Rule object |
规则数据定义 |
|
targets |
Array of Target Object |
目标数据定义 |
Common对象:
|
字段名 |
类型 |
说明 |
|---|---|---|
|
channel_id |
Int64 |
通道ID |
|
channel_id_ex |
Int64 |
相机扩展通道ID |
|
pts |
Int64 |
时间戳 |
|
sdc_device_id |
String |
主从机设备ID |
|
sdc_uuid |
String |
摄像机视频源通道号 |
|
intelligence_type |
Int |
智能类型 |
|
image_height |
Int |
图片高度 |
|
image_width |
Int |
图片宽度 |
|
meta_type_mask |
Int |
元数据类型掩码 枚举值:
|
|
intelligent_target_index |
Int |
智能目标/业务类型索引 |
|
target_time_domain_info |
Int |
配合索引使用,标识三层数据时域信息 枚举值:
|
Rule 对象:
|
字段名 |
类型 |
说明 |
|---|---|---|
|
rule_area_pos |
MetaArea Object |
规则框位置 |
|
rule_area_pos_relative |
MetaArea Object |
规则框位置(相对位置) |
|
rule_type |
Int |
规则类型 |
|
字段名 |
类型 |
说明 |
|---|---|---|
|
data_id |
Int |
数据ID,正常情况下不为空,必传 |
|
panorama_pic |
String |
全景图,已经转化为url |
|
panorama_pic_size |
Int |
全景图大小 |
|
pic_snapshot_dst_offset |
Int64 |
夏令时偏移时间:单位秒/s |
|
pic_snapshot_time |
Int |
抓拍时间:单位秒/s |
|
pic_snapshot_timems |
Int64 |
抓拍时间:单位毫秒/ms |
|
pic_snapshot_tzone |
Int64 |
抓拍时区:单位毫秒/ms 东区为+ 西区为- |
|
color |
Color object |
颜色 |
|
global_object_id |
Int64 |
智能目标全局ID |
|
obj_id |
Int |
目标ID |
|
obj_pos |
Rect object |
目标位置 |
|
obj_pos_r |
Rect object |
目标位置(相对位置) |
|
obj_speed |
Point object |
目标速度 |
|
obj_status |
Int |
目标状态 枚举值:
|
|
obj_type |
Int |
目标类型 枚举值:
|
|
target_type |
Int |
智能业务场景 枚举值:
|
|
字段名 |
类型 |
说明 |
|---|---|---|
|
x |
Int |
上层业务检测框左上角坐标点计算方式,x1 = x *全景图像素宽度/ 10000 |
|
y |
Int |
上层业务检测框左上角坐标点计算方式,y1 = y *全景图像素高度/ 10000 |
|
width |
Int |
上层业务检测框宽度计算方式 widht1 = widht *全景图像素宽度/ 10000 |
|
height |
Int |
上层业务检测框长度计算方式 height1 = height *全景图像素高度/ 10000 |
{
"message_id": 1676822987447548758,
"message_type": "behavior_analysis_data",
"data": {
"device_id": "HOLO123***",
"channel_id": "0",
"data_id": "167682298743800500010002rwnwv040",
"report_time": "2023-02-20T00:09:47+08:00",
"data": {
"common": {
"channel_id": 101,
"channel_id_ex": 101,
"image_height": 1440,
"image_width": 2560,
"intelligent_target_index": 281474976710656,
"meta_type_mask": 2,
"pts": 517577328,
"sdc_uuid": "e15ee2b3-83c2-073a-28e1-378e9612aa71",
"target_time_domain_info": 1,
"target_type": 21
},
"rule": {
"rule_area_pos": {
"num": 4,
"points": [
{
"x": 1,
"y": 1
},
{
"x": 351,
"y": 1
},
{
"x": 351,
"y": 287
},
{
"x": 1,
"y": 287
}
]
},
"rule_area_pos_relative": {
"num": 4,
"points": [
{
"x": 28,
"y": 34
},
{
"x": 9971,
"y": 34
},
{
"x": 9971,
"y": 9965
},
{
"x": 28,
"y": 9965
}
]
},
"rule_type": 4
},
"targets": [
{
"data_id": "167682298742100500010001rwnwv040",
"panorama_pic": "https://www.example.com/v1/holo/tlv_HOLO123***_0_20230220_tlv_167682298742100500010001rwnwv040.jpg/static",
"panorama_pic_size": 199629,
"pic_snapshot_dst_offset": 0,
"pic_snapshot_time": 1631497728,
"pic_snapshot_timems": 1631497728392,
"pic_snapshot_tzone": 28800000,
"target_type": 21
},
{
"color": {
"red": 0,
"green": 0,
"blue": 0,
"conf_lev": 0,
"color_id": 0
},
"data_id": "167682298743800500010000rwnwv040",
"global_object_id": 7007351688747024516,
"meta_type_mask": 2,
"obj_id": 132,
"obj_pos": {
"x": 169,
"y": 110,
"width": 74,
"height": 177
},
"obj_pos_r": {
"x": 4804,
"y": 3819,
"width": 2128,
"height": 6173
},
"obj_speed": {
"x": 0,
"y": 0
},
"obj_status": 16,
"obj_type": 98,
"target_type": 21
},
{
"color": {
"red": 0,
"green": 0,
"blue": 0,
"conf_lev": 0,
"color_id": 0
},
"data_id": "167682298743800500010001rwnwv040",
"global_object_id": 7007351688747024510,
"meta_type_mask": 2,
"obj_id": 126,
"obj_pos": {
"x": 217,
"y": 155,
"width": 80,
"height": 126
},
"obj_pos_r": {
"x": 6191,
"y": 5395,
"width": 2285,
"height": 4388
},
"obj_speed": {
"x": 8,
"y": 14
},
"obj_status": 16,
"obj_type": 98,
"target_type": 21
},
{
"color": {
"red": 0,
"green": 0,
"blue": 0,
"conf_lev": 0,
"color_id": 0
},
"data_id": "167682298743800500010002rwnwv040",
"global_object_id": 7007351688747024493,
"meta_type_mask": 2,
"obj_id": 109,
"obj_pos": {
"x": 85,
"y": 137,
"width": 74,
"height": 148
},
"obj_pos_r": {
"x": 2421,
"y": 4756,
"width": 2128,
"height": 5152
},
"obj_speed": {
"x": 3,
"y": 6
},
"obj_status": 16,
"obj_type": 98,
"target_type": 21
}
]
}
},
"test": false
}