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技能执行结果

Hi 您好,本文档主要介绍EM-BOX各技能执行的输出结果。

1 技能执行结果

1.1 电子围栏

字段名 类型 备注 样例
persons List 人员信息
+score Double 置信度,置信度大于等于人体检测阈值的才会返回,小于阈值的会被过滤掉
+top Int 人体框左上角顶点距离图片上边界的像素
+left Int 人体框左上角顶点距离图片左边界的像素
+width Int 人体框宽度
+height Int 人体框高度
normal boolean 该结果是否正常,如果不正常则触发告警:
true:正常,不触发告警;
false:不正常,触发告警

示例:

{
  "persons": [
    {
      "score": 0.964915931224823,
      "top": 413,
      "left": 707,
      "width": 136,
      "height": 304
    },
    {
      "score": 0.9301413893699646,
      "top": 426,
      "left": 903,
      "width": 203,
      "height": 291
    }
  ],
  "normal": false
}

1.2 陌生人识别

字段名 类型 备注 样例
strangers List 陌生人列表
+score Double 人体置信度
+hasFace Boolean 是否检测到人脸
++faceLocation Object 人脸位置
+++top Int 人脸框左上角顶点距离图片上边界的像素
+++left Int 人脸框左上角顶点距离图片左边界的像素
+++width Int 人脸框宽度
+++height Int 人脸框高度
+faceSimilarityScore Double 人脸相似度得分(0-100)
+doubtful Boolean 是否可疑人员
+stranger Boolean 是否陌生人
+inFaceSet Boolean 是否在人脸库中
+top Int 人体框左上角顶点距离图片上边界的像素
+left Int 人体框左上角顶点距离图片左边界的像素
+width Int 人体框宽度
+height Int 人体框高度
acquaintances List 非陌生人列表(即识别出在人脸库中的人)
大部分属性与strangers重合,只列举有差别的部分
+groupId String 所属人脸组id
+userId String 人脸用户id
+userName String 人脸用户名
normal Boolean 该结果是否正常,如果不正常则触发告警:
true:正常,不触发告警;
false:不正常,触发告警

示例:

{
    "normal":false,
    "strangers":[
        {
            "score":0.49294501543045044,
            "faceLocation":{
                "top":810,
                "left":1445,
                "width":45,
                "height":66
            },
            "hasFace":true,
            "top":734,
            "left":1236,
            "width":300,
            "faceSimilarityScore":0,
            "doubtful":false,
            "stranger":true,
            "height":330,
            "inFaceSet":false
        },
        {
            "score":0.4093378484249115,
            "hasFace":false,
            "top":827,
            "left":157,
            "width":382,
            "doubtful":true,
            "stranger":true,
            "height":244
        }
    ],
    "acquaintances":[
        {
            "groupId":"egde_001",
            "faceSimilarityScore":99.79257202148438,
            "doubtful":false,
            "userName":"1",
            "userId":"huge",
            "inFaceSet":true,
            "score":0.9727230072021484,
            "faceLocation":{
                "top":147,
                "left":197,
                "width":238,
                "height":320
            },
            "hasFace":true,
            "top":19,
            "left":9,
            "width":624,
            "stranger":false,
            "height":790
        }
    ]
}

1.3 烟火检测

字段名 类型 备注 样例
smokeNum Int 烟的数量
fireNum Int 火的数量
normal Boolean 该结果是否正常,如果不正常则触发告警:
true:正常,不触发告警;
false:不正常,触发告警
result List
+classname String 分类:
fire:火
smoke:烟
+probability Double 置信度
+location Object 坐标
++top Int 烟火框左上角顶点距离图片上边界的像素
++left Int 烟火框左上角顶点距离图片左边界的像素
++width Int 烟火框宽度
++height Int 烟火框高度

示例:

{
  "result": [
    {
      "classname": "fire",
      "probability": 0.2966460883617401,
      "location": {
        "top": 680,
        "left": 1172,
        "width": 43,
        "height": 39
      }
    },
    {
      "classname": "smoke",
      "probability": 0.2966460883617401,
      "location": {
        "top": 68,
        "left": 172,
        "width": 49,
        "height": 69
      }
    }
  ],
  "normal": false,
  "smokeNum": 1,
  "fireNum": 1
}

1.4 安全帽检测

字段名 类型 备注 样例
normal boolean 该结果是否正常,如果不正常则触发告警:
true:正常,不触发告警;
false:不正常,触发告警
personsWearingHelmet List 佩戴安全帽的人
+matchRatio Double 佩戴置信度
+location Object 人体坐标
++score Double 人体置信度
++top Int 人体左上角顶点距离图片上边界的像素
++left Int 人体左上角顶点距离图片左边界的像素
++width Int 人体框宽度
++height Int 人体框高度
+helmet Object 安全帽信息
++color Int 安全帽颜色
++classname String 分类,一般都为safety-helmet
++probability Double 安全帽置信度
++location Object 安全帽坐标
+++top Int 安全帽左上角顶点距离图片上边界的像素
+++left Int 安全帽左上角顶点距离图片左边界的像素
+++width Int 安全帽宽度
+++height Int 安全帽高度
personsNotWearingHelmet List 未佩戴安全帽的人(属性跟上边类似)

示例:

{
  "normal": false,
  "personsWearingHelmet": [
    {
      "helmet": {
        "color": 3,
        "classname": "safety-helmet",
        "probability": 0.6903132796287537,
        "location": {
          "top": 53,
          "left": 356,
          "width": 96,
          "height": 117
        }
      },
      "location": {
        "score": 0.9604066610336304,
        "top": 50,
        "left": 349,
        "width": 367,
        "height": 401
      },
      "matchRatio": 1
    },
    {
      "helmet": {
        "color": 2,
        "classname": "safety-helmet",
        "probability": 0.6452111005783081,
        "location": {
          "top": 202,
          "left": 85,
          "width": 24,
          "height": 16
        }
      },
      "location": {
        "score": 0.31597423553466797,
        "top": 202,
        "left": 64,
        "width": 56,
        "height": 171
      },
      "matchRatio": 1
    }
  ],
  "personsNotWearingHelmet": [
    {
      "helmet": {
        "probability": 0
      },
      "location": {
        "score": 0.8570256233215332,
        "top": 177,
        "left": 104,
        "width": 68,
        "height": 193
      },
      "matchRatio": 0
    }
  ]
}

1.5 攀高检测

字段名 类型 备注 样例
person_num Int 总人数
climbingPersonNum Int 攀高人员数量
noClimbingPersonNum Int 非攀高人员数量
person_info Array 人员信息
+location JSON 人员位置信息(图片上的人体框就是根据这个结果画上去的)
++score Double 置信度,置信度大于等于人体检测阈值的才会返回,小于阈值的会被过滤掉
++top Double 人体框左上角顶点距离图片上边界的像素
++left Double 人体框左上角顶点距离图片左边界的像素
++width Double 人体框宽度
++height Double 人体框高度
climbingPersonList Array 攀高人员列表,结构同person_info
noClimbingPersonList Array 非攀高人员列表,结构同person_info

示例:

{
  "person_num": 1,
  "climbingPersonList": [
    {
      "hasClimbing": "true",
      "location": {
        "score": 0.96569776535034,
        "top": 474.64399777926,
        "left": 770.71929931641,
        "width": 185.22188626803,
        "height": 434.34442960299
      }
    }
  ],
  "person_info": [
    {
      "hasClimbing": "true",
      "location": {
        "score": 0.96569776535034,
        "top": 474.64399777926,
        "left": 770.71929931641,
        "width": 185.22188626803,
        "height": 434.34442960299
      }
    }
  ],
  "noClimbingPersonNum": 0,
  "climbingPersonNum": 1
}

1.6 easydl物体检测

字段名 类型 备注 样例
labels Array 检测出的标签列表
+confidence Double 置信度
+label String label名称
+boundingBox JSON 该label的物体框坐标
++top Double 物体框左上角顶点距离图片上边界的像素
++left Double 物体框左上角顶点距离图片左边界的像素
++width Double 物体框宽度
++height Double 物体框高度
+x1 Double 推荐直接使用boundingBox.left,x1= boundingBox.left/图片宽度
+y1 Double 推荐直接使用boundingBox.top,y1= boundingBox.top/图片高度
+x2 Double 含义参考x1,只不过x2代表的是物体框右下角顶点
+y2 Double 含义参考y1,只不过y2代表的是物体框右下角顶点

示例:

{
  "labels": [
    {
      "confidence": 0.94091796875,
      "index": 1,
      "label": "airplane",
      "x1": 0.19151463508605956,
      "y1": 0.1457286685705185,
      "x2": 0.24310667037963868,
      "y2": 0.629201066493988,
      "boundingBox": {
        "left": 245.13873291015625,
        "top": 104.92464137077332,
        "width": 66.03780517578127,
        "height": 348.100126504898
      }
    },
    {
      "confidence": 0.64091796875,
      "index": 1,
      "label": "test",
      "x1": 0.29151463508605957,
      "y1": 0.2457286685705185,
      "x2": 0.34310667037963866,
      "y2": 0.529201066493988,
      "boundingBox": {
        "left": 373.13873291015625,
        "top": 176.92464137077332,
        "width": 66.03780517578122,
        "height": 204.10012650489807
      }
    },
    {
      "confidence": 0.64091796875,
      "index": 1,
      "label": "ant",
      "x1": 0.29151463508605957,
      "y1": 0.5457286685705185,
      "x2": 0.6431066703796386,
      "y2": 0.7292010664939881,
      "boundingBox": {
        "left": 373.13873291015625,
        "top": 392.9246413707733,
        "width": 450.03780517578116,
        "height": 132.10012650489807
      }
    },
    {
      "confidence": 0.74091796875,
      "index": 1,
      "label": "angel",
      "x1": 0.29151463508605957,
      "y1": 0.045728668570518494,
      "x2": 0.7831066703796387,
      "y2": 0.32920106649398806,
      "boundingBox": {
        "left": 373.13873291015625,
        "top": 32.924641370773315,
        "width": 629.2378051757812,
        "height": 204.1001265048981
      }
    }
  ]
}

1.7 easydl图像分类

字段名 类型 备注 样例
labels Array 检测出的标签列表
+confidence Double 置信度
+label String 分类名称

示例:

{
  "labels": [
    {
      "confidence": 0.79,
      "index": 1,
      "label": "cat"
    }
  ]
}

1.8 人流过密预警

字段名 类型 备注 样例
peopleNumThreshold Int 人流密度阀值
isTooMany String 人流是否过密
areas Array 框选的检测区域
+nodes Array 框选的检测区域的各个顶点

示例

{
  "peopleNumThreshold": 1,
  "person_num": 2,
  "isTooMany": "true",
  "areas": [
    {
      "nodes": [
        [
          72,
          84
        ],
        [
          1792,
          57
        ],
        [
          1780,
          983
        ],
        [
          169,
          975
        ]
      ],
      "style": {
        "color": "blue",
        "stroke": {
          "width": 3
        },
        "renderType": 1
      },
      "hasEvent": true
    }
  ]
}

1.9 离岗检测

字段名 类型 备注 样例
state String 是否离岗
areas Array 框选的检测区域
+nodes Array 框选的检测区域的各个顶点

示例

{
  "state": "leave",
  "areas": [
    {
      "nodes": [
        [
          3,
          1
        ],
        [
          -3,
          478
        ],
        [
          636,
          476
        ],
        [
          637,
          3
        ]
      ],
      "style": {
        "color": "blue",
        "stroke": {
          "width": 3
        },
        "renderType": 1
      },
      "hasEvent": false
    }
  ]
}

1.10 课堂专注度

字段名 类型 备注 样例
average_attention Double 平均专注度
face_num Int 识别的人脸数量
face_list Array 识别的人脸列表
+expression JSON 眼神
++probability Double 置信度(下同)
++type String 类型
+face_shape JSON 脸部姿势
+beauty Double 漂亮程度
+face_shape JSON 脸部姿势
+gender JSON 性别
+face_probability Double 人脸置信度
+quality JSON 人脸质量
++illumination Double 光照
++occlusion JSON !
+++nose Double 鼻子
+++right_eye Double 右眼
+++mouth Double 嘴巴
+++left_cheek Double 左颊
+++left_eye Double 左眼
+++chin_contour Double 轮廓
+++right_cheek Double 右颊
++blur Double 模糊度
++completeness Double 完整度
+glasses JSON 眼镜
+face_type JSON 脸部类型
+angle JSON 角度
++roll Double 绕z轴旋转角度
++pitch Double 绕x轴旋转角度
++yaw Double 绕y轴旋转角度
+attention Double 专注度
+face_token String 人脸Token
+location JSON 人脸位置信息
+age Double 年龄
areas Array 框选的检测区域
+nodes Array 框选的检测区域的各个顶点

示例

{
  "average_attention": 83.31,
  "face_num": 2,
  "face_list": [
    {
      "expression": {
        "probability": 1.0,
        "type": "none"
      },
      "face_shape": {
        "probability": 0.85,
        "type": "round"
      },
      "beauty": 39.3,
      "gender": {
        "probability": 1.0,
        "type": "male"
      },
      "face_probability": 1.0,
      "quality": {
        "illumination": 149.0,
        "occlusion": {
          "nose": 0.0,
          "right_eye": 0.0,
          "mouth": 0.0,
          "left_cheek": 0.07,
          "left_eye": 0.06,
          "chin_contour": 0.06,
          "right_cheek": 0.03
        },
        "blur": 0.0,
        "completeness": 0
      },
      "glasses": {
        "probability": 1.0,
        "type": "none"
      },
      "face_type": {
        "probability": 1.0,
        "type": "human"
      },
      "angle": {
        "roll": -10.91,
        "pitch": 20.23,
        "yaw": 26.46
      },
      "attention": 80.58,
      "face_token": "b441f5c91de5eb0c03262bcca4355d4c",
      "location": {
        "top": 542,
        "left": 261,
        "rotation": -6,
        "width": 234,
        "height": 192
      },
      "age": 28.0
    },
    {
      "expression": {
        "probability": 0.99,
        "type": "none"
      },
      "face_shape": {
        "probability": 0.44,
        "type": "round"
      },
      "beauty": 19.88,
      "gender": {
        "probability": 0.54,
        "type": "male"
      },
      "face_probability": 0.97,
      "quality": {
        "illumination": 62.0,
        "occlusion": {
          "nose": 0.73,
          "right_eye": 0.37,
          "mouth": 0.57,
          "left_cheek": 0.23,
          "left_eye": 0.39,
          "chin_contour": 0.25,
          "right_cheek": 1.0
        },
        "blur": 0.99,
        "completeness": 1
      },
      "glasses": {
        "probability": 0.99,
        "type": "none"
      },
      "face_type": {
        "probability": 0.89,
        "type": "human"
      },
      "angle": {
        "roll": -174.94,
        "pitch": 10.68,
        "yaw": -24.18
      },
      "attention": 86.03,
      "face_token": "0b07a67dbb2c9cdf7178c29e244e5cb9",
      "location": {
        "top": 414,
        "left": 1048,
        "rotation": -175,
        "width": 24,
        "height": 24
      },
      "age": 22.0
    }
  ]
}

1.11 车辆违停分析

字段名 类型 备注 样例
vehicleNum Int 识别到的车数量
areas Array 框选的检测区域
+nodes Array 框选的检测区域的各个顶点
vehicle_info Array 识别到的车辆信息
+license JSON 车牌信息
++number String 车牌号
++location JSON 识别到的车牌位置
++probability Double 置信度
++typeInChinese String 车辆类型(中文)
++location JSON 识别到的车辆位置
++type String 车辆类型

示例

{
  "log_id": 7567754712735709974,
  "vehicleNum": 1,
  "areas": [
    {
      "nodes": [
        [
          592,
          527
        ],
        [
          668,
          1061
        ],
        [
          1729,
          1065
        ],
        [
          1631,
          726
        ],
        [
          949,
          740
        ],
        [
          845,
          588
        ]
      ],
      "style": {
        "color": "blue",
        "stroke": {
          "width": 3
        },
        "renderType": 1
      },
      "hasEvent": true
    }
  ],
  "vehicle_info": [
    {
      "license": {
        "number": "无",
        "location": {
          "left": 0.0,
          "top": 0.0,
          "width": 0.0,
          "height": 0.0
        }
      },
      "probability": 0.4867725670337677,
      "typeInChinese": "卡车",
      "location": {
        "top": 653,
        "left": 910,
        "width": 68,
        "height": 71
      },
      "type": "truck"
    }
  ],
  "vehicle_num": 1
}
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