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Radio (single-choice)

Single-choice radio classification

Radio classifications can be applied at the global level and can be nested within an object-type annotation. Use radio classifications when only one option/answer is possible.

Import

Python SDK

Radio is a type of ClassificationAnnotation.

Definition

Radio(answer = ClassificationAnswer(name = "OPTION_NAME"))

ParameterValue
answerClassificationAnswer

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.

radio_annotation = Radio(answer = ClassificationAnswer(name = "second_radio_answer"))

##Creating a label with radio annotation
ground_truth_list = LabelList()
data = VideoData(uid = datarow.uid)
annotation = ClassificationAnnotation(name="CLASSIFICATION_FEATURE_NAME", value = radio_annotation)
ground_truth_list.append(Label(data = data, annotations = [annotation]))

bbox_with_radio_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="radio_class_name",
      		value=Radio(answer=ClassificationAnswer(name="radio_answer_name"))
    )
  ]
)

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.
answer.schemaIdImage
Video
Text
Audio
Document
Tiled imagery		YesThe ID of the radio answer schema. Radio can only have one correct answer so "answer" is singular.
frames.startVideoYesThe first frame you wish to include in the radio classification.
frames.endVideoYesThe last frame you wish to include in the radio classification.

Supported data types

Data typeSupported
Images, Video, Text, HTML, DICOM, Tiled and Document- Yes for global classifications
- Partially yes for nested classifications within an object are supported only if the root object annotation type is supported on the respective data type.

Format

// 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
            }
        }
    ]
}

// For global classifications, do not include the frames section
{
   "schemaId": "ckd1295hc00640z0uapvm1xbd",  // question schema id
   "uuid": "fb72782d-f6ed-43ba-8677-77b03197392d",
   "dataRow": {
       "id": "ckd1299m8cqbs0cq43mju1bvp"
    },
    "answer": {
        "schemaId": "ckd1295jn00760z0u01hw4yz5" // answer schema id
    },
    "frames": [
        {
            "start": 7,
            "end": 13,
        },
        {
            "start": 18,
            "end": 19,
        }
    ]
}

// 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
            }
        }
    ]
}

// Global classification
{
    "uuid": "1278daa6-ce64-4363-be24-4fa5eadffb17",
    "dataRow": {
        "id": "ckd11jg6scq9c0cq43vmh6i07"
    },  
    "schemaId": "ckd11j3yk000c0z0u4xn6dc4r", // Radio question
    "answer": {
        "schemaId": "ckd11j415000u0z0ubu7ee4w2" // Radio answer
    }
}

// Nested classification
{ 
    "uuid": "9fd9a92e-2560-4e77-81d4-b2e955800092", 
    "schemaId": "ck8kukafkqx1a0880iczbrqym",
    "dataRow": { 
        "id": "ck1s02fqxm8fi0757f0e6qtdc" 
    }, 
    "location": { 
        "start": 67, 
        "end": 128 
    },
    "classifications": [
        {
            "schemaId": "ckshluz847d9d0yb65oqhfg65", // Nested radio question
            "answer": {
                "schemaId": "ckshluz8r7d9j0yb6d9l45o1b" // Nested radio 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
            }
        }
    ]
}

// 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 Radio classifications from Labelbox, the export file will contain the following information for each Radio.

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
Conversation		ID of the classification question in the ontology.
schemaIdImage
Video
Text
Audio
Document
Tiled imagery
Conversation		ID of the schema that contains all of the structural information for the classification question.
titleImage
Video
Text
Audio
Document
Tiled imagery
Conversation		Text that appears as the classification question.
valueImage
Video
Text
Audio
Document
Tiled imagery
Conversation		Name of the classification question in the Labelbox database.
messageIdConversationThis only applies to radio classifications configured as "Frame/Pixel based" for conversational assets.

This corresponds to the messageId of the conversational file.
answer.featureIdImage
Video
Text
Audio
Document
Tiled imagery
Conversation		ID of the classification answer in the ontology.
answer.schemaIdImage
Video
Text
Audio
Document
Tiled imagery
Conversation		ID of the schema that contains the structural information for the classification answer.
answer.titleImage
Video
Text
Audio
Document
Tiled imagery
Conversation		Text that appears as the classification answer.
answer.valueImage
Video
Text
Audio
Document
Tiled imagery
Conversation		Name of the classification answer in the Labelbox database.
answer.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": "ckmuuwmp4000a3g68rmku827s",
    "schemaId": "ckmuuvs5p5nj40y629l1570bi",
    "title": "Is it daytime?",
    "value": "is_it_daytime?",
    "answer": {
        "featureId": "ckmuuwmp400093g68qof3hnt8",
        "schemaId": "ckmuuvs7u5njg0y629iiuc216",
        "title": "Yes",
        "value": "yes"
    }
}

{
    "featureId": "cknp365y41fk60y9y7nz7faqt",
    "schemaId": "ckmvaijzd2elz0y8h06ribh9b",
    "title": "Is it daytime?",
    "value": "is_it_daytime?",
    "answer": {
        "featureId": "cknp365y41fka0y9ydabe7be4",
        "schemaId": "ckmvaik0p2eml0y8h12z632kq",
        "title": "Yes",
        "value": "yes",
        "keyframe": false
    }
}

{
    "featureId": "cknp3d0hw00013g68wkjemi6o",
    "schemaId": "cknp3ctst06nq0ycte8icc2l3",
    "title": "Is it daytime?",
    "value": "is_it_daytime?",
    "answer": {
        "featureId": "cknp3d0hw00003g685c0nj5c1",
        "schemaId": "cknp3cttx06oe0yct3f0d6pmz",
        "title": "Yes",
        "value": "yes"
    }
}

{
    "featureId": "ckmuuwmp4000a3g68rmku827s",
    "schemaId": "ckmuuvs5p5nj40y629l1570bi",
    "title": "Is it daytime?",
    "value": "is_it_daytime?",
    "answer": {
        "featureId": "ckmuuwmp400093g68qof3hnt8",
        "schemaId": "ckmuuvs7u5njg0y629iiuc216",
        "title": "Yes",
        "value": "yes"
    }
}

{
    "featureId": "cknp3d0hw00013g68wkjemi6o",
    "schemaId": "cknp3ctst06nq0ycte8icc2l3",
    "title": "Is it daytime?",
    "value": "is_it_daytime?",
    "answer": {
        "featureId": "cknp3d0hw00003g685c0nj5c1",
        "schemaId": "cknp3cttx06oe0yct3f0d6pmz",
        "title": "Yes",
        "value": "yes"
    }
}

{
    "featureId": "ckmuuwmp4000a3g68rmku827s",
    "schemaId": "ckmuuvs5p5nj40y629l1570bi",
    "title": "Is it daytime?",
    "value": "is_it_daytime?",
    "answer": {
        "featureId": "ckmuuwmp400093g68qof3hnt8",
        "schemaId": "ckmuuvs7u5njg0y629iiuc216",
        "title": "Yes",
        "value": "yes"
    }
}

{
    "featureId": "cknp3d0hw00013g68wkjemi6o",
    "schemaId": "cknp3ctst06nq0ycte8icc2l3",
    "title": "user sentiment",
    "value": "user sentiment?",
    "messageId": "1",
    "answer": {
        "featureId": "cknp3d0hw00003g685c0nj5c1",
        "schemaId": "cknp3cttx06oe0yct3f0d6pmz",
        "title": "Positive",
        "value": "Positive"
    }
}