Multi-choice checklist classification

Checklist classifications can be applied at the global level and can be nested within an object-type annotation. Use checklist classifications when more than option/answer is possible.

Import

Python SDK

Checklist is a type of ClassificationAnnotation.

Definition

Checklist(answer=List[ClassificationAnswer])

ParameterValue
answerList of ClassificationAnswer

Supported data types

Data typeSupported
Images, Video, Text, HTML, DICOM, Tiled and Document- Yes for global classifications

- Partially yes for nested classifications

🚧

Nested classifications with annotation types

In order to import a nested classification with annotation types, the following conditions must be met:

  • Must be nested under an ObjectAnnotation
  • Root ObjectAnnotation type must be supported on the respective data type

Importing nested classifications within classifications is currently not supported in the Python SDK. Use NDJSON format instead.

checklist_annotation = Checklist(answer=[ClassificationAnswer(name="first_checklist_answer"),ClassificationAnswer(name="second_checklist_answer")])
bbox_with_checklist_subclass = ObjectAnnotation(
    name="bounding_box_class_name",
    value=Rectangle(
        start=Point(x=0, y=0), # Top left
        end=Point(x=10, y=10), # Bottom right
    ),
    classifications=[
        ClassificationAnnotation(
            name="checklist_class_name",
            value=Checklist(
                answer=[ClassificationAnswer(name="first_checklist_answer"),
                        ClassificationAnswer(name="second_checklist_answer")]
            )
        )
    ]
)

NDJSON

NDJSON format is recommended if an annotation type is not yet supported in Python SDK or if you are unable to use the Python environment.

Definition

ParameterAsset typeRequiredDescription
uuidImage
Video
Text
Audio
Document
Tiled imagery
YesA user-generated UUID for each annotation. If you import an annotation to a Data Row and there is already an imported annotation with the same uuid on that Data Row, the latest import will override the previous one. The uuid must be 128 bits (32 characters). The following formats are supported:

- A0EEBC99-9C0B-4EF8-BB6D-6BB9BD380A11

- {a0eebc99-9c0b-4ef8-bb6d-6bb9bd380a11}

- a0eebc999c0b4ef8bb6d6bb9bd380a11

- a0ee-bc99-9c0b-4ef8-bb6d-6bb9-bd38-0a11

- {a0eebc99-9c0b4ef8-bb6d6bb9-bd380a11}
schemaIdImage
Video
Text
Audio
Document
Tiled imagery
YesThe ID of the schema that contains all of the information needed for rendering your annotation.
dataRow.idImage
Video
Text
Audio
Document
Tiled imagery
YesThe ID of the Data Row where you want to attach the imported annotations.
answers.schemaIdImage
Video
Text
Audio
Document
Tiled imagery
YesThe ID of the Checklist answer schema. Checklist can have multiple correct answers so "answers" is plural.
frames.startVideoYesThe first frame you wish to include in the checklist classification.
frames.endVideoYesThe last frame you wish to include in the checklist classification.

Supported data types

Data typeSupported
Images, Text, HTML, DICOM, Tiled and Document- Yes for global and classifications
- Yes for nested classifications if the parent objectAnnotation is supported
Video- Yes for global and classifications
- Yes for nested classifications if the parent objectAnnotation is supported
- Only single-level classification is supported on frame level

Format

// Global classification
{
    "uuid": "fb72782d-f6ed-43ba-8677-77b03197392d",
    "dataRow": {
        "id": "ckd1299m8cqbs0cq43mju1bvp"
    },
    "schemaId": "ckd1295hc00640z0uapvm1xbd", // Checklist question
    "answers": [
        {
            "schemaId": "ckd1295jn00760z0u01hw4yz5" // Checklist answer
        },
        {
            "schemaId": "ckd1295hh006g0z0ucbxgfgec" // Checklist answer
        }
    ]
}

// Nested classification
{
    "uuid": "532953e6-746f-4d74-945d-b4a9c2786479",
    "schemaId": "ckshluz7h7d9b0yb60biaasya",
    "dataRow": {
        "id": "ckshkj1vj4rsq0yvubkoe76vi"
    },
    "bbox": {
        "top": 57,
        "left": 209,
        "height": 216,
        "width": 152
    },
    "classifications": [
        {
            "schemaId": "ckshluz847d9d0yb65oqhfg65", // Nested checklist question
            "answers": [
                    {
                        "schemaId": "ckshluz8r7d9j0yb6d9l45o1b" // Nested checklist answer
                    },
                    {
                        "schemaId": "ckshluz8r7d9j0yb6d9l45opl" // Nested checklist answer
                    },                  
            ]
        }
    ]
}
// Global classification only
{
    "schemaId": "ckd1295hc00640z0uapvm1xbd",  // question schema id
    "uuid": "fb72782d-f6ed-43ba-8677-77b03197392d",
    "dataRow": {
    "id": "ckd1299m8cqbs0cq43mju1bvp"
    },
    "answers": [
        {
            "schemaId": "ckd1295jn00760z0u01hw4yz5" // answer schema id
        }, {
            "schemaId": "ckd1295hh006g0z0ucbxgfgec" // answer schema id
        }
    ],
    "frames": [
        {
            "start": 7,
            "end": 13,
        },
        {
            "start": 18,
            "end": 19,
        }
    ]
}
// Global classification
{
    "uuid": "fb72782d-f6ed-43ba-8677-77b03197392d",
    "dataRow": {
        "id": "ckd1299m8cqbs0cq43mju1bvp"
    },
    "schemaId": "ckd1295hc00640z0uapvm1xbd", // Checklist question
    "answers": [
        {
            "schemaId": "ckd1295jn00760z0u01hw4yz5" // Checklist answer
        },
        {
            "schemaId": "ckd1295hh006g0z0ucbxgfgec" // Checklist answer
        }
    ]
}

// Nested classification
{ 
    "uuid": "9fd9a92e-2560-4e77-81d4-b2e955800092", 
    "schemaId": "ck8kukafkqx1a0880iczbrqym",
    "dataRow": { 
        "id": "ck1s02fqxm8fi0757f0e6qtdc" 
    }, 
    "location": { 
        "start": 67, 
        "end": 128 
    },
    "classifications": [
        {
            "schemaId": "ckshluz847d9d0yb65oqhfg65", // Nested checklist question
                        "answers": [
                        {
                            "schemaId": "ckd1295jn00760z0u01hw4yz5" // Checklist answer
                        },
                        {
                            "schemaId": "ckd1295hh006g0z0ucbxgfgec" // Checklist answer
                        }
                    ]
        }
    ]
}
// Global classification
{
    "uuid": "fb72782d-f6ed-43ba-8677-77b03197392d",
    "dataRow": {
        "id": "ckd1299m8cqbs0cq43mju1bvp"
    },
    "schemaId": "ckd1295hc00640z0uapvm1xbd", // Checklist question
    "answers": [
        {
            "schemaId": "ckd1295jn00760z0u01hw4yz5" // Checklist answer
        },
        {
            "schemaId": "ckd1295hh006g0z0ucbxgfgec" // Checklist answer
        }
    ]
}

// Nested classification
{
    "uuid": "532953e6-746f-4d74-945d-b4a9c2786479",
    "schemaId": "ckshluz7h7d9b0yb60biaasya",
    "dataRow": {
        "id": "ckshkj1vj4rsq0yvubkoe76vi"
    },
    "bbox": {
        "top": 57,
        "left": 209,
        "height": 216,
        "width": 152
    },
    "classifications": [
        {
            "schemaId": "ckshluz847d9d0yb65oqhfg65", // Nested checklist question
            "answers": [
                    {
                        "schemaId": "ckshluz8r7d9j0yb6d9l45o1b" // Nested checklist answer
                    },
                    {
                        "schemaId": "ckshluz8r7d9j0yb6d9l45opl" // Nested checklist answer
                    },                  
            ]
        }
    ]
}
// Global classification
{
    "uuid": "fb72782d-f6ed-43ba-8677-77b03197392d",
    "dataRow": {
        "id": "ckd1299m8cqbs0cq43mju1bvp"
    },
    "schemaId": "ckd1295hc00640z0uapvm1xbd", // Checklist question
    "answers": [
        {
            "schemaId": "ckd1295jn00760z0u01hw4yz5" // Checklist answer
        },
        {
            "schemaId": "ckd1295hh006g0z0ucbxgfgec" // Checklist answer
        }
    ]
}

// Nested classification
{
    "uuid": "532953e6-746f-4d74-945d-b4a9c2786479",
    "schemaId": "ckshluz7h7d9b0yb60biaasya",
    "dataRow": {
        "id": "ckshkj1vj4rsq0yvubkoe76vi"
    },
    "bbox": {
        "top": 57,
        "left": 209,
        "height": 216,
        "width": 152
    },
    "classifications": [
        {
            "schemaId": "ckshluz847d9d0yb65oqhfg65", // Nested checklist question
            "answers": [
                    {
                        "schemaId": "ckshluz8r7d9j0yb6d9l45o1b" // Nested checklist answer
                    },
                    {
                        "schemaId": "ckshluz8r7d9j0yb6d9l45opl" // Nested checklist answer
                    },                  
            ]
        }
    ]
}
// Global classification
{
    "uuid": "1278daa6-ce64-4363-be24-4fa5eadffb17",
    "dataRow": {
        "id": "ckd11jg6scq9c0cq43vmh6i07"
    },  
    "schemaId": "ckd11j3yk000c0z0u4xn6dc4r", // Radio question
    "answer": {
        "schemaId": "ckd11j415000u0z0ubu7ee4w2" // Radio answer
    }
}

// Nested classification
{
    "uuid": "532953e6-746f-4d74-945d-b4a9c2786479",
    "schemaId": "ckshluz7h7d9b0yb60biaasya",
    "dataRow": {
        "id": "ckshkj1vj4rsq0yvubkoe76vi"
    },
    "bbox": {
        "top": 57,
        "left": 209,
        "height": 216,
        "width": 152
    },
    "classifications": [
        {
            "schemaId": "ckshluz847d9d0yb65oqhfg65", // Nested radio question
            "answer": {
                "schemaId": "ckshluz8r7d9j0yb6d9l45o1b" // Nested radio answer
            }
        }
    ]
}

Export

When you export your Checklist classifications from Labelbox, the export file will contain the following information for each Checklist.

Python SDK

The export format of the polygon is similar to the import format.

Learn more about exporting annotations using the SDK here

JSON

You will receive a JSON file when you generate an export from the app.

ParameterAsset typeDescription
featureIdImage
Video
Text
Audio
Document
Tiled imagery
ID of the classification question in the ontology.
schemaIdImage
Video
Text
Audio
Document
Tiled imagery
ID of the schema that contains all of the structural information for the classification question.
titleImage
Video
Text
Audio
Document
Tiled imagery
Text that appears as the classification question.
valueImage
Video
Text
Audio
Document
Tiled imagery
Name of the classification question in the Labelbox database.
answers.featureIdImage
Video
Text
Audio
Document
Tiled imagery
ID of the classification answer in the ontology.
answers.schemaIdImage
Video
Text
Audio
Document
Tiled imagery
ID of the schema that contains the structural information for the classification answer.
answers.titleImage
Video
Text
Audio
Document
Tiled imagery
Text that appears as the classification answer.
answers.valueImage
Video
Text
Audio
Document
Tiled imagery
Name of the classification answer in the Labelbox database.
answers.keyframeVideoWhen keyframe is true, it means that a labeler created or made an adjustment to the annotation on that frame. When keyframe is false, it means the annotation was auto-populated or interpolated on that frame.

Format

{
  "featureId": "cl89b1d3g00013b6k8388lpol",
  "schemaId": "cl89b186w0xg107xkga0fdf4j",
  "scope": "global",
  "title": "Attributes",
  "value": "attributes",
  "answers": [
    {
      "featureId": "cl89b1dln00033b6ky6j9cb62",
      "schemaId": "cl89b186w0xg407xk4yvkf3o8",
      "title": "Crowded",
      "value": "crowded"
    },
    {
      "featureId": "cl89b1e3z00063b6kll28e559",
      "schemaId": "cl89b186w0xg607xk8ogy304a",
      "title": "Foot traffic",
      "value": "foot_traffic"
    },
    {
      "featureId": "cl89b1ekd000a3b6kbiipqxi7",
      "schemaId": "cl89b186w0xg807xke5kg606w",
      "title": "Vehicle traffic",
      "value": "vehicle_traffic"
    }
  ]
}
[
  {
    "frameNumber": 1,
    "classifications": [
      {
        "featureId": "cl89b9sjb00003b6keuil18qx",
        "schemaId": "cl89b9kwz11yj070nhmnscwj4",
        "title": "Signs in frame",
        "value": "signs_in_frame",
        "answers": [
          {
            "featureId": "cl89b9sjb00013b6kvxfa6gmj",
            "schemaId": "cl89b9kwz11yk070na20ngv31",
            "title": "Stop",
            "value": "stop",
            "keyframe": true
          },
          {
            "featureId": "cl89b9tq000023b6ke9jh90ym",
            "schemaId": "cl89b9kwz11ym070nbr0m7qbs",
            "title": "Yield",
            "value": "yield",
            "keyframe": true
          }
        ]
      }
    ],
    "objects": [],
    "relationships": []
  },
  {
    "frameNumber": 2,
    "classifications": [
      {
        "featureId": "cl89b9sjb00003b6keuil18qx",
        "schemaId": "cl89b9kwz11yj070nhmnscwj4",
        "title": "Signs in frame",
        "value": "signs_in_frame",
        "answers": [
          {
            "featureId": "cl89b9sjb00013b6kvxfa6gmj",
            "schemaId": "cl89b9kwz11yk070na20ngv31",
            "title": "Stop",
            "value": "stop",
            "keyframe": false
          },
          {
            "featureId": "cl89b9tq000023b6ke9jh90ym",
            "schemaId": "cl89b9kwz11ym070nbr0m7qbs",
            "title": "Yield",
            "value": "yield",
            "keyframe": false
          }
        ]
      }
    ],
    "objects": [],
    "relationships": []
  },
  {
    "frameNumber": 3,
    "classifications": [
      {
        "featureId": "cl89b9sjb00003b6keuil18qx",
        "schemaId": "cl89b9kwz11yj070nhmnscwj4",
        "title": "Signs in frame",
        "value": "signs_in_frame",
        "answers": [
          {
            "featureId": "cl89b9sjb00013b6kvxfa6gmj",
            "schemaId": "cl89b9kwz11yk070na20ngv31",
            "title": "Stop",
            "value": "stop",
            "keyframe": false
          },
          {
            "featureId": "cl89b9tq000023b6ke9jh90ym",
            "schemaId": "cl89b9kwz11ym070nbr0m7qbs",
            "title": "Yield",
            "value": "yield",
            "keyframe": false
          }
        ]
      }
    ],
    "objects": [],
    "relationships": []
  },
  {
    "frameNumber": 4,
    "classifications": [
      {
        "featureId": "cl89b9sjb00003b6keuil18qx",
        "schemaId": "cl89b9kwz11yj070nhmnscwj4",
        "title": "Signs in frame",
        "value": "signs_in_frame",
        "answers": [
          {
            "featureId": "cl89b9sjb00013b6kvxfa6gmj",
            "schemaId": "cl89b9kwz11yk070na20ngv31",
            "title": "Stop",
            "value": "stop",
            "keyframe": false
          },
          {
            "featureId": "cl89b9tq000023b6ke9jh90ym",
            "schemaId": "cl89b9kwz11ym070nbr0m7qbs",
            "title": "Yield",
            "value": "yield",
            "keyframe": false
          }
        ]
      }
    ],
    "objects": [],
    "relationships": []
  },
  {
    "frameNumber": 5,
    "classifications": [
      {
        "featureId": "cl89b9sjb00003b6keuil18qx",
        "schemaId": "cl89b9kwz11yj070nhmnscwj4",
        "title": "Signs in frame",
        "value": "signs_in_frame",
        "answers": [
          {
            "featureId": "cl89b9sjb00013b6kvxfa6gmj",
            "schemaId": "cl89b9kwz11yk070na20ngv31",
            "title": "Stop",
            "value": "stop",
            "keyframe": true
          },
          {
            "featureId": "cl89b9tq000023b6ke9jh90ym",
            "schemaId": "cl89b9kwz11ym070nbr0m7qbs",
            "title": "Yield",
            "value": "yield",
            "keyframe": true
          }
        ]
      }
    ],
    "objects": [],
    "relationships": []
  },
  {
    "frameNumber": 12,
    "classifications": [
      {
        "featureId": "cl89b9sjb00003b6keuil18qx",
        "schemaId": "cl89b9kwz11yj070nhmnscwj4",
        "title": "Signs in frame",
        "value": "signs_in_frame",
        "answers": [
          {
            "featureId": "cl89b9tq000023b6ke9jh90ym",
            "schemaId": "cl89b9kwz11ym070nbr0m7qbs",
            "title": "Yield",
            "value": "yield",
            "keyframe": true
          },
          {
            "featureId": "cl89badlf00033b6kxnrwfamq",
            "schemaId": "cl89b9kwz11yo070nfrwieccb",
            "title": "Hazard",
            "value": "hazard",
            "keyframe": true
          }
        ]
      }
    ],
    "objects": [],
    "relationships": []
  },
  {
    "frameNumber": 13,
    "classifications": [
      {
        "featureId": "cl89b9sjb00003b6keuil18qx",
        "schemaId": "cl89b9kwz11yj070nhmnscwj4",
        "title": "Signs in frame",
        "value": "signs_in_frame",
        "answers": [
          {
            "featureId": "cl89b9tq000023b6ke9jh90ym",
            "schemaId": "cl89b9kwz11ym070nbr0m7qbs",
            "title": "Yield",
            "value": "yield",
            "keyframe": false
          },
          {
            "featureId": "cl89badlf00033b6kxnrwfamq",
            "schemaId": "cl89b9kwz11yo070nfrwieccb",
            "title": "Hazard",
            "value": "hazard",
            "keyframe": false
          }
        ]
      }
    ],
    "objects": [],
    "relationships": []
  },
  {
    "frameNumber": 14,
    "classifications": [
      {
        "featureId": "cl89b9sjb00003b6keuil18qx",
        "schemaId": "cl89b9kwz11yj070nhmnscwj4",
        "title": "Signs in frame",
        "value": "signs_in_frame",
        "answers": [
          {
            "featureId": "cl89b9tq000023b6ke9jh90ym",
            "schemaId": "cl89b9kwz11ym070nbr0m7qbs",
            "title": "Yield",
            "value": "yield",
            "keyframe": false
          },
          {
            "featureId": "cl89badlf00033b6kxnrwfamq",
            "schemaId": "cl89b9kwz11yo070nfrwieccb",
            "title": "Hazard",
            "value": "hazard",
            "keyframe": false
          }
        ]
      }
    ],
    "objects": [],
    "relationships": []
  },
  {
    "frameNumber": 15,
    "classifications": [
      {
        "featureId": "cl89b9sjb00003b6keuil18qx",
        "schemaId": "cl89b9kwz11yj070nhmnscwj4",
        "title": "Signs in frame",
        "value": "signs_in_frame",
        "answers": [
          {
            "featureId": "cl89b9tq000023b6ke9jh90ym",
            "schemaId": "cl89b9kwz11ym070nbr0m7qbs",
            "title": "Yield",
            "value": "yield",
            "keyframe": false
          },
          {
            "featureId": "cl89badlf00033b6kxnrwfamq",
            "schemaId": "cl89b9kwz11yo070nfrwieccb",
            "title": "Hazard",
            "value": "hazard",
            "keyframe": false
          }
        ]
      }
    ],
    "objects": [],
    "relationships": []
  },
  {
    "frameNumber": 16,
    "classifications": [
      {
        "featureId": "cl89b9sjb00003b6keuil18qx",
        "schemaId": "cl89b9kwz11yj070nhmnscwj4",
        "title": "Signs in frame",
        "value": "signs_in_frame",
        "answers": [
          {
            "featureId": "cl89b9tq000023b6ke9jh90ym",
            "schemaId": "cl89b9kwz11ym070nbr0m7qbs",
            "title": "Yield",
            "value": "yield",
            "keyframe": false
          },
          {
            "featureId": "cl89badlf00033b6kxnrwfamq",
            "schemaId": "cl89b9kwz11yo070nfrwieccb",
            "title": "Hazard",
            "value": "hazard",
            "keyframe": false
          }
        ]
      }
    ],
    "objects": [],
    "relationships": []
  },
  {
    "frameNumber": 17,
    "classifications": [
      {
        "featureId": "cl89b9sjb00003b6keuil18qx",
        "schemaId": "cl89b9kwz11yj070nhmnscwj4",
        "title": "Signs in frame",
        "value": "signs_in_frame",
        "answers": [
          {
            "featureId": "cl89b9tq000023b6ke9jh90ym",
            "schemaId": "cl89b9kwz11ym070nbr0m7qbs",
            "title": "Yield",
            "value": "yield",
            "keyframe": true
          },
          {
            "featureId": "cl89badlf00033b6kxnrwfamq",
            "schemaId": "cl89b9kwz11yo070nfrwieccb",
            "title": "Hazard",
            "value": "hazard",
            "keyframe": true
          }
        ]
      }
    ],
    "objects": [],
    "relationships": []
  },
  {
    "frameNumber": 21,
    "classifications": [
      {
        "featureId": "cl89b9sjb00003b6keuil18qx",
        "schemaId": "cl89b9kwz11yj070nhmnscwj4",
        "title": "Signs in frame",
        "value": "signs_in_frame",
        "answers": [
          {
            "featureId": "cl89b9sjb00013b6kvxfa6gmj",
            "schemaId": "cl89b9kwz11yk070na20ngv31",
            "title": "Stop",
            "value": "stop",
            "keyframe": true
          }
        ]
      }
    ],
    "objects": [],
    "relationships": []
  },
  {
    "frameNumber": 22,
    "classifications": [
      {
        "featureId": "cl89b9sjb00003b6keuil18qx",
        "schemaId": "cl89b9kwz11yj070nhmnscwj4",
        "title": "Signs in frame",
        "value": "signs_in_frame",
        "answers": [
          {
            "featureId": "cl89b9sjb00013b6kvxfa6gmj",
            "schemaId": "cl89b9kwz11yk070na20ngv31",
            "title": "Stop",
            "value": "stop",
            "keyframe": false
          }
        ]
      }
    ],
    "objects": [],
    "relationships": []
  },
  {
    "frameNumber": 23,
    "classifications": [
      {
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