vehicle_data 机非人业务
功能介绍
机非人业务:机动车/非机动车/行人相关的智能场景。
机非人业务消息体的message_type值为target_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:
- 6 机非人业务目标整体信息(摄像机SDC/NVR800开启机非人模式,行人进入区域,会被自动抓拍,提取行人特征信息,如:年龄段、是否戴眼镜、长头发还是短头发、是否戴帽子、衣服款式和颜色等)
- 7 机非人业务机动车信息(摄像机SDC/NVR800开启机非人模式, 机动车进入区域,会被自动抓拍,提取机动车特征信息,如:机动车品牌、款型、车牌号、车牌颜色等)
- 8 机非人业务非机动车信息(摄像机SDC/NVR800开启机非人模式,非机动车进入区域,会被自动抓拍,提取非机动车特征信息,如:非机动车类型、颜色、骑行者的特征信息等)
- 53 非机动车上目标检测(特定混行摄像机SDC开启混行模式,非机动车进入区域,会被自动抓拍,提取非机动车及其骑行者特征信息,如:非机动车类型、颜色、骑行者的特征信息等。注意:与8不同的是,53有更多的关于骑行者的特征信息,如骑行者是否背包、是否有撑伞等)
消息结构体介绍
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 |
itgt_type | Int | 智能业务场景 枚举值:
|
report_time | String | 上报时间,示例:2021-03-15T16:43:00+08:00 |
global_obj_id | Int64 | 全局ID,设备传入的唯一标识 |
lane_id | Int64 | 车道号 |
vehicle_direction | Int | 车辆运动方向 枚举值:
|
plate_char | String | 车牌字符,当检测到机动车属性时传该值 |
plate_color | Int | 车牌颜色,当检测到机动车属性时传该值,见附录车牌颜色 |
vehicle_type | Int | 机非人类型,当检测到机非人属性时传该值,见附录机非人类型 |
vehicle_color | Int | 车辆颜色,当检测到机动车属性时传该值,见附录车辆颜色 |
car_pre_brand | Int | 品牌字符索引,当检测到机动车属性时传该值,见附录车款类型 |
car_sub_brand | Int | 子款符号索引,当检测到机动车属性时传该值 |
car_year_brand | String | 年款符号,当检测到机动车属性时传该值 |
rider_age_range | Int | 骑行人年龄范围 枚举值:
|
rider_gender | Int | 骑行人性别 枚举值:
|
has_helmet | Boolen | 是否戴头盔 |
helmet_color | Int | 头盔颜色 |
motor_color | Int | 非机动车颜色 |
has_motor_sunshade | Boolen | 是否有遮阳伞 |
has_motor_carry | Boolen | 是否有携带物 |
has_license_plate | Boolen | 是否有车牌 |
rider_num | Int | 骑行人数 |
motor_type | Int | 非机动车类型 |
vehicle_url | String | 车辆特写图url |
target_all_pic_url | String | 目标整体抠图url |
panorama_url | String | 全景图片url |
vehicle_pos | RectCor object | 车辆检测框位置万分比 |
human_pos | RectCor object | 目标整体位置万分比 |
human_age | Int | 行人年龄 枚举值:
|
human_gender | Int | 行人性别 枚举值:
|
human_upperstyle | Int | 上衣款式
|
human_uppercolor | Int | 上衣颜色 |
human_lowstyle | Int | 下衣款式 |
human_lowercolor | Int | 下衣颜色 |
human_shape | Int | 体型 |
human_mouthmask | Int | 行人口罩 |
human_hair | Int | 行人头发 |
common | Common object | 通用数据定义 |
target | Target object | 目标:设备上传TLV时的设备的原始数据,该字段是设备上传的原始数据的解析,不同的业务场景传入的字段会不相同。 |
moto_type | Int | 非机动车类型 |
字段名 | 类型 | 说明 |
|---|---|---|
x_cor | Int | 上层业务检测框左上角坐标点x计算方式,x1 =x_cor *全景图像素宽度/ 10000 |
y_cor | Int | 上层业务检测框左上角坐标点y计算方式,y1 =y_cor *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 |
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:
|
字段名 | 类型 | 说明 |
|---|---|---|
car_pre_brand | String | 品牌字符:中文字符,例如大众 |
car_pre_brand_index | Int | 品牌字符索引,当检测到机动车属性时传该值,见附录车款类型 |
car_sub_brand | String | 子款字符:中文字符,例如明锐 |
car_sub_brand_index | Int | 子款字符索引 |
car_year_brand | String | 年款字符:例如2011 |
cur_snap_index | Int | 当前抓拍序列号 |
global_object_id | Int64 | 智能目标全局ID |
human_pic | String | 目标整体抠图:已转化为图片url |
human_pic_kps | Int | 目标整体抠图kps质量过滤标志位 |
human_pic_roi | Rect object | 目标整体抠图中的目标整体目标框:目标整体抠图中可能存在其它干扰,此坐标用于精确圈定目标整体范围 |
human_rect_position | Rect object | 目标整体位置 |
lane_id | Int | 车道号 |
panorama_pic | String | 全景图:已转化为图片url |
pic_snapshot_dst_offset | Int64 | 夏令时偏移时间:单位秒/s |
pic_snapshot_time | Int | 抓拍时间 |
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-,支持夏令时 |
plate_char | String | 车牌字符,当检测到机动车属性时传该值 |
plate_color | Int | 车牌颜色,当检测到机动车属性时传该值,见附录车牌颜色 |
plate_pic | String | 车牌抠图:已转化为图片url |
plate_pos | Rect object | 车牌位置万分比 |
plate_pos_abs | Rect object | 车牌位置绝对坐标 |
plate_pos_com | Rect object | 车牌位置万分比 |
plate_type | Int | 车牌类型,参考附录车牌类型 |
target_type | Int | 智能业务场景 枚举值:
|
trecord_type | Int | 告警类型,见附录告警类型 |
vehicle_color | Int | 车辆颜色,当检测到机动车属性时传该值,见附录车辆颜色 |
vehicle_direction | Int | 车辆运动方向 枚举值:
|
vehicle_pic | String | 车辆图,已转化为图片url |
vehicle_pos | Rect object | 车身位置万分比 |
vehicle_pos_abs | Rect object | 车辆位置绝对坐标 |
vehicle_pos_com | Rect object | 车辆位置相对坐标万分比 |
vehicle_type | Int | 机非人类型,当检测到机非人属性时传该值,见附录机非人类型 |
vehicle_type_ext | Int | 机非人扩展类型,当检测到机非人属性时传该值,见附录机非人类型 ,例如机非人类型为轿车,扩展类型为两厢轿车 |
vhd_object_id | Int64 | 机非人ID |
human_gender | Int | 行人性别 枚举值:
|
human_umbrella | Int | 是否撑伞 枚举值:
|
human_lower_color | Int | 下衣颜色 枚举值:
|
human_direct | Int | 行进方向 |
human_carry | Int | 是否拎东西 枚举值:
|
human_mouth_mask | Int | 是否戴口罩 枚举值:
|
human_age | Int | 年龄人群 枚举值:
|
human_upper_texture | Int | 上衣纹理 枚举值:
|
human_view | Int | 朝向 枚举值:
|
human_feature | Feature Object | 目标整体属性 |
human_luggage | Int | 是否有行李箱 |
human_backpack | Int | 是否有背包 |
human_lower_style | Int | 下衣款式 枚举值:
|
human_upper_color | Int | 上衣颜色 |
human_hair | Int | 发型 枚举值:
|
human_shape | Int | 体型 枚举值:
|
human_speed | Int | 行进速度 |
human_upper_style | Int | 上衣款式 枚举值:
|
human_hat | Int | 是否戴帽子 |
human_frontpack | Int | 是否有前面背包 |
human_satchel | Int | 是否有斜挎包 |
human_glass | Int | 是否戴眼镜 |
motor_color | Int | 非机动车颜色 |
motor_license_plate | Int | 是否有车牌 |
motor_motor_carry | Int | 是否有携带物品 |
motor_sunshade | Int | 是否有遮阳伞 |
motor_sunshade_color | Int | 遮阳伞颜色 |
motor_type | Int | 非机动车类型 |
riderman_age | Int | 骑行人年龄人群 |
riderman_feature | RidermanFeature Object | 骑行人属性 |
riderman_gender | Int | 骑行人性别 |
riderman_helmet | Int | 骑行人是否戴头盔 |
riderman_helmetcolor | Int | 骑行人头盔颜色 |
riderman_num | Int | 骑行人数量,具体人数 |
riderman_uppercolor | Int | 骑行人上衣颜色 |
riderman_upperstyle | Int | 骑行人上衣款式 |
vehicle_pos_abs | Rect Object | 车辆位置绝对坐标 |
face_id | Int64 | 人脸号 |
face_pic_time | Int | 人脸抓拍时间 |
face_pic_tzone | Int64 | 人脸抓拍时区:单位毫秒/ms 东区为+ 西区为-,支持夏令时 |
字段名 | 类型 | 说明 |
|---|---|---|
x | Int | 上层业务检测框左上角坐标点x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y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 |
字段名 | 类型 | 说明 |
|---|---|---|
age | Int | 年龄人群 |
backpack | Int | 是否有背包 |
carry | Int | 是否拎东西 |
front_pack | Int | 是否有前面背包 |
gender | Int | 行人性别 枚举值:
|
glass | Int | 是否戴眼睛 |
hair | Int | 发型 |
hat | Int | 是否戴麦子 |
lower_color | Int | 上衣颜色 |
lower_style | Int | 上衣款式 |
luggage | Int | 是否有行李箱 |
mouth_mask | Int | 是否戴口罩 |
move_direct | Int | 行进方向 |
move_speed | Int | 行进速度 |
satchel | Int | 是否有斜挎包 |
shape | Int | 体型 |
umbrella | Int | 是否有雨伞 |
upper_color | Int | 下衣颜色 |
upper_style | Int | 下衣款式 |
upper_texture | Int | 上衣纹理 |
view | Int | 朝向 |
字段名 | 类型 | 说明 |
|---|---|---|
age | Int | 年龄人群 |
gender | Int | 行人性别 枚举值:
|
helmet | Int | 是否戴头盔 |
helmet_color | Int | 头盔颜色 |
upper_color | Int | 下衣颜色 |
upper_style | Int | 下衣款式 |
{
"message_id": 1676253459558286045,
"message_type": "vehicle_data",
"data": {
"device_id": "219123456CYP***",
"channel_id": "0",
"data_id": "167625345941400200060000rwnwv130",
"report_time": "2023-02-13T09:57:37+08:00",
"itgt_type": 6,
"global_obj_id": 7198857782190185688,
"lane_id": 1,
"vehicle_type": 9,
"target_all_pic_url": "https://www.example.com/v1/holo/tlv_219123456CYP***_0_20230213_tlv_167625345941400200040000rwnwv130.jpg/static",
"panorama_url": "https://www.example.com/v1/holo/tlv_219123456CYP***_0_20230213_tlv_167625345941400200020000rwnwv130.jpg/static",
"human_lowstyle": 1,
"human_gender": 1,
"human_uppercolor": 2,
"human_hair": 2,
"human_shape": 1,
"human_age": 2,
"human_mouthmask": 1,
"human_lowercolor": 2,
"human_upperstyle": 2,
"human_pos": {
"x_cor": 3218,
"y_cor": 1601,
"width": 1057,
"height": 6046
},
"common": {
"channel_id": 101,
"channel_id_ex": 101,
"meta_type_mask": 2,
"pts": 167668079703,
"sdc_device_id": "40619954-b309-46b1-7d1a-a3f443a58c87",
"sdc_uuid": "224440c1-966e-57eb-fd7b-8ca03739be7e"
},
"target": {
"global_object_id": 7198857782190185688,
"human_pic": "https://www.example.com/v1/holo/tlv_219123456CYP***_0_20230213_tlv_167625345941400200040000rwnwv130.jpg/static",
"human_pic_roi": {
"x": 2916,
"y": 0,
"width": 4229,
"height": 10000
},
"human_gender": 1,
"human_umbrella": 1,
"human_lower_color": 2,
"human_direct": 2,
"human_carry": 1,
"human_mouth_mask": 1,
"human_age": 2,
"human_upper_texture": 1,
"human_view": 1,
"human_feature": {
"age": 2,
"backpack": 1,
"carry": 1,
"front_pack": 1,
"gender": 1,
"glass": 65536,
"hair": 2,
"hat": 65536,
"lower_color": 2,
"lower_style": 1,
"luggage": 1,
"mouth_mask": 1,
"move_direct": 2,
"move_speed": 0,
"satchel": 1,
"shape": 1,
"umbrella": 1,
"upper_color": 2,
"upper_style": 2,
"upper_texture": 1,
"view": 131072
},
"human_luggage": 1,
"human_backpack": 1,
"human_lower_style": 1,
"human_upper_color": 2,
"human_hair": 2,
"human_shape": 1,
"human_speed": 2,
"human_upper_style": 2,
"human_hat": 1,
"human_frontpack": 1,
"human_satchel": 1,
"human_glass": 1,
"human_rect_position": {
"x": 3218,
"y": 1601,
"width": 1057,
"height": 6046
},
"lane_id": 1,
"panorama_pic": "https://www.example.com/v1/holo/tlv_219123456CYP***_0_20230213_tlv_167625345941400200020000rwnwv130.jpg/static",
"pic_snapshot_dst_offset": 0,
"pic_snapshot_time": 1676253453,
"pic_snapshot_timems": 1676253453434,
"pic_snapshot_tzone": 28800000,
"target_type": 6,
"trecord_type": 34,
"vehicle_type": 9,
"vehicle_type_ext": 9,
"vhd_object_id": 40152
}
},
"test": false
} {
"message_id": 1676252528838941764,
"message_type": "vehicle_data",
"data": {
"device_id": "219123456CYP***",
"channel_id": "0",
"data_id": "167625252854900210110000rwnwv130",
"report_time": "2023-02-13T09:42:06+08:00",
"itgt_type": 7,
"global_obj_id": 7198857782190185052,
"lane_id": 2,
"vehicle_direction": 4,
"plate_char": "浙XXXXXX",
"plate_color": 1,
"vehicle_type": 1,
"vehicle_color": 2,
"car_pre_brand": 74,
"car_sub_brand": 554,
"car_year_brand": "2010",
"vehicle_url": "https://www.example.com/v1/holo/tlv_219123456CYP***_0_20230213_tlv_167625252854900210010000rwnwv130.jpg/static",
"panorama_url": "https://www.example.com/v1/holo/tlv_219123456CYP***_0_20230213_tlv_167625252854900210020000rwnwv130.jpg/static",
"vehicle_pos": {
"x_cor": 3218,
"y_cor": 111,
"width": 3085,
"height": 3402
},
"common": {
"channel_id": 101,
"channel_id_ex": 101,
"meta_type_mask": 2,
"pts": 166735159705,
"sdc_uuid": "224440c1-966e-57eb-fd7b-8ca03739be7e",
"sdc_device_id": "40619954-b309-46b1-7d1a-a3f443a58c87"
},
"target": {
"car_pre_brand": "斯柯达",
"car_pre_brand_index": 74,
"car_sub_brand": "明锐",
"car_sub_brand_index": 554,
"car_year_brand": "2010",
"cur_snap_index": 0,
"global_object_id": 7198857782190185052,
"lane_id": 2,
"panorama_pic": "https://www.example.com/v1/holo/tlv_219123456CYP***_0_20230213_tlv_167625252854900210020000rwnwv130.jpg/static",
"pic_snapshot_dst_offset": 0,
"pic_snapshot_time": 1676252525,
"pic_snapshot_timems": 1676252525274,
"pic_snapshot_tzone": 28800000,
"plate_char": "浙XXXXXX",
"plate_color": 1,
"plate_pic": "https://www.example.com/v1/holo/tlv_219123456CYP***_0_20230213_tlv_167625252854900210080000rwnwv130.jpg/static",
"plate_pos": {
"x": 5437,
"y": 1958,
"width": 601,
"height": 666
},
"plate_pos_abs": {
"x": 696,
"y": 141,
"width": 77,
"height": 48
},
"plate_pos_com": {
"x": 5437,
"y": 1958,
"width": 601,
"height": 666
},
"plate_type": 1,
"target_type": 7,
"trecord_type": 34,
"vehicle_color": 2,
"vehicle_direction": 4,
"vehicle_pic": "https://www.example.com/v1/holo/tlv_219123456CYP***_0_20230213_tlv_167625252854900210010000rwnwv130.jpg/static",
"vehicle_pos": {
"x": 3218,
"y": 111,
"width": 3085,
"height": 3402
},
"vehicle_pos_abs": {
"x": 412,
"y": 8,
"width": 395,
"height": 245
},
"vehicle_pos_com": {
"x": 3218,
"y": 111,
"width": 3085,
"height": 3402
},
"vehicle_type": 1,
"vehicle_type_ext": 17,
"vhd_object_id": 39516
}
},
"test": false
} {
"message_id": 1676253298093565055,
"message_type": "vehicle_data",
"data": {
"device_id": "219123456CYP***",
"channel_id": "0",
"data_id": "167625329805000220030000rwnwv130",
"report_time": "2023-02-13T09:54:56+08:00",
"itgt_type": 8,
"moto_type": 1,
"motor_color": 1,
"rider_num": 1,
"global_obj_id": 7198857782190185592,
"lane_id": 2,
"vehicle_type": 8,
"vehicle_url": "https://www.example.com/v1/holo/tlv_219123456CYP***_0_20230213_tlv_167625329805000220010000rwnwv130.jpg/static",
"panorama_url": "https://www.example.com/v1/holo/tlv_219123456CYP***_0_20230213_tlv_167625329805000220020000rwnwv130.jpg/static",
"vehicle_pos": {
"x_cor": 3484,
"y_cor": 3805,
"width": 1953,
"height": 6180
},
"common": {
"channel_id": 101,
"channel_id_ex": 101,
"image_height": 720,
"image_width": 1280,
"meta_type_mask": 2,
"pts": 167506599705,
"sdc_uuid": "224440c1-966e-57eb-fd7b-8ca03739be7e"
},
"target": {
"motor_color": 1,
"motor_license_plate": 1,
"motor_motor_carry": 1,
"motor_sunshade": 1,
"motor_sunshade_color": 0,
"motor_type": 1,
"riderman_age": 0,
"riderman_feature": {
"age": 0,
"gender": 0,
"helmet": 0,
"helmet_color": 0,
"upper_color": 0,
"upper_style": 0
},
"riderman_gender": 0,
"riderman_helmet": 0,
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"vehicle_pos_abs": {
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},
"test": false
} {
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"data": {
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"vehicle_url": "https://www.example.com/v1/holo/tlv_219123456CYP***_0_20230213_tlv_167625329805000220010000rwnwv130.jpg/static",
"panorama_url": "https://www.example.com/v1/holo/tlv_219123456CYP***_0_20230213_tlv_167625329805000220020000rwnwv130.jpg/static",
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"human_pic_kps": 1,
"human_pic_roi": {
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"pic_snapshot_dst_offset": 0,
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"vehicle_pos": {
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},
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} 
