自动驾驶云服务 OCTOPUS-预审核模型文件:预审核结果格式说明

时间:2024-10-30 16:07:41

预审核结果格式说明

审核完毕后,需要按照规定格式组织预标注结果,并保存在特定路径(TARGET_RESULT_DIR)下的json文件中。路径要求见镜像制作(标注)

Json文件内容组织结构如下所示,labels字段中保存每个对象的标注信息、审核模型预测信息(predict_infos)和审核结果信息(inspection)。

{ 
   "labels":[{ 
      #1. 此对象的标注信息 (直接从源数据labels.json中获取),如果未标注出此对象,则无此部分信息
          … …
      #2.此对象的模型预测信息 ,如果模型未预测出此对象,则无此部分信息
      "predict_infos": {
        #形状坐标信息
        #对象类别名称
        #额外属性信息
      }
      #3.审核结果,如果未审核此对象,则无此部分信息
      "inspection": { 
      #字段名称取自OCTPS_INSPECTION_ATTRI_DIR文件
       } 
   },
       … …
] 
}

其中3D大规模点云分割任务还包含“labels_ext”和“predict_labels_ext”字段,具体参考“3D大规模点云分割”。

{ 
         "labels":[], 
         "labels_ext":{ } 
         "predict_labels":[]
}

以2D目标检测为例,完整json结果文件样例如下:

{ 
  "labels": [ 
  { 
       #1. 此对象的标注信息(直接从源数据labels.json中获取) 
      "label_meta_id": 1846, 
      "bndbox": { 
        "ymin": 545.4334, 
        "xmin": 1158.3188, 
        "ymax": 705.71844, 
        "xmax": 1436.3274 
      }, 
      "name": "框0504", 
      "shape_type": "bndbox", 
      "serial_number": 2, 
      "label_object_id": 2, 
      "attribute": "{\"优先级\":\"1\"}", 
      "label_meta_name": "框0504", 
       #2.此对象的模型预测信息 
      "predict_infos": { 
        "bndbox": { 
          "ymin": 545.4334, 
          "xmin": 1158.3188, 
          "ymax": 725.71844, 
          "xmax": 1456.3274 
        }, 
        "label_meta_name": "框0504", 
        "attribute": "{\"优先级\":\"1\"}" 
      }, 
      #3.审核结果
      "inspection": { 
        #字段名称取自OCTPS_INSPECTION_ATTRI_DIR文件
        "miss_label_error": false, 
        "vehicle_direction_error": false, 
        "error_desc": "无效", 
        "attribute_error": true, 
        "out_range_label_error": true, 
        "anchor_error": false, 
        "classification_error": false, 
        "extra_label_error": false 
      } 
    } 
  ] 
}

不同类型的标注对象形状基本信息所需格式不同。下面为各类标注对象predict_infos的字段说明:

2D目标检测

{"predict_infos": { 
        "bndbox": { 
          "ymin": 545.4334, 
          "xmin": 1158.3188, 
          "ymax": 725.71844, 
          "xmax": 1456.3274 
        }, 
        "label_meta_name": "框0504", 
        "attribute": "{\"优先级\":\"1\"}" 
      }
}

2D语义分割

{"predict_infos": {
        "polygon": {
          "size": 3,
          "points": [
            {
              "xpoint": 135.03,
              "ypoint": 482.94937
            },
            {
              "xpoint": 84.318344,
              "ypoint": 554.4891
            },
            {
              "xpoint": 135.03,
              "ypoint": 482.94937
            }
          ]
        },
        "label_meta_name": "多边形0504",
        "attribute": "{\"优先级\":\"1\"}"
      }
}

2D车道线

{"predict_infos": {
        "line": {
          "size": 3,
          "points": [
            {
              "xpoint": 901.138,
              "ypoint": 553.583
            },
            {
              "xpoint": 741.36,
              "ypoint": 630.367
            },
            {
              "xpoint": 618.153,
              "ypoint": 681.566
            }
          ]
        },
        "label_meta_name": "线0504",
        "attribute": "{\"优先级\":\"1\"}"
      }
}

3D目标检测:

{
  "predict_infos": {
    "label_meta_name": "Car",
    "cube_3d": {
      "rotation": {
        "x": 0.0,
        "y": 0.0,
        "z": 0.08726646
      },
      "location": {
        "x": -40.23651584555386,
        "y": 1.2362389665094042,
        "z": -0.8413386615781039
      },
      "attribute": "{}",
      "dimensions": {
        "length": 4.459540762142082,
        "width": 1.4870339632034302,
        "height": 1.4895729290943762
      }
    }
  }
}

3D大规模点云分割:

{"predict_infos": {
        "polygon_3d_v2": {
          "ascii_char": "2"
        },
        "name": "car",
      }
}

3D大规模点云分割完整样例

{
  "labels": [
    {
      "label_meta_id": 4867,
      "create_time": 0,
      "polygon_3d_v2": {
        "ascii_char": "3"
      },
      "name": "car",
      "shape_type": "polygon_3d_v2",
      "serial_number": 0,
      "label_object_id": -1,
      "attribute": "",
      "label_meta_name": "car",
      "inspection": {
        "miss_label_error": false,
        "vehicle_direction_error": false,
        "error_desc": "",
        "attribute_error": false,
        "out_range_label_error": false,
        "anchor_error": false,
        "classification_error": false,
        "extra_label_error": false
      },
      "predict_infos": {
        "polygon_3d_v2": {
          "ascii_char": "2"
        },
        "name": "car"
      }
    },
    {
      "predict_infos": {
        "polygon_3d_v2": {
          "ascii_char": "4"
        },
        "name": "van"
      }
    }
  ],
  "labels_ext": {
    "ascii_string": "3333333333          3333333333"
  },
  "predict_labels_ext": {
    "ascii_string": "222222222244444     2222222222"
  }
}

labels_ext中保存点云中每个点的标注类别,具体内容说明参考OCTOPUS数据集格式说明。predict_labels_ext中保存点云中每个点的模型预测类别。

3D语义分割审核结果可视化说明:针对有审核属性错误的标注对象,展示该标注对象对应位置点的预测类别。

support.huaweicloud.com/usermanual-octopus/octopus-04-0037.html