Labeling Service Dashboard

class labelbox.schema.labeling_service_dashboard.LabelingServiceDashboard(*, id: str, name: str, createdAt: datetime | None = None, updatedAt: datetime | None = None, createdById: str | None = None, status: LabelingServiceStatus | None = None, dataRowsCount: int, tasksCompletedCount: int, tasksRemainingCount: int | None = None, mediaType: MediaType | None = None, editorTaskType: EditorTaskType | None = None, tags: List[LabelingServiceDashboardTags] | None = None, client: Any)[source]

Bases: _CamelCaseMixin

Represent labeling service data for a project

NOTE on tasks vs data rows. A task is a unit of work that is assigned to a user. A data row is a unit of data that needs to be labeled.

In the current implementation a task represents a single data row. However tasks only exists when a labeler start labeling a data row. So if a data row is not labeled, it will not have a task associated with it. Therefore the number of tasks can be less than the number of data rows.

id

project id

Type:

str

name

project name

Type:

str

status

status of the labeling service

Type:

LabelingServiceStatus

data_rows_count

total number of data rows batched in the project

Type:

int

tasks_completed_count

number of tasks completed (in the Done queue)

Type:

int

tasks_remaining_count

number of tasks remaining (i.e. tasks in progress), None if labeling has not started

Type:

int

tags

tags associated with the project

Type:

List[LabelingServiceDashboardTags]

media_type

media type of the project

Type:

MediaType

editor_task_type

editor task type of the project

Type:

EditorTaskType

client

labelbox client

Type:

Any

classmethod get(client, project_id: str) LabelingServiceDashboard[source]

Returns the labeling service associated with the project.

Raises:

ResourceNotFoundError – If the project does not have a labeling service.

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'alias_generator': <function to_camel>, 'arbitrary_types_allowed': True, 'populate_by_name': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'client': FieldInfo(annotation=Any, required=True, alias='client', alias_priority=1), 'created_at': FieldInfo(annotation=Union[datetime, NoneType], required=False, default=None, alias='createdAt', alias_priority=1, frozen=True), 'created_by_id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, alias='createdById', alias_priority=1, frozen=True), 'data_rows_count': FieldInfo(annotation=int, required=True, alias='dataRowsCount', alias_priority=1, frozen=True), 'editor_task_type': FieldInfo(annotation=Union[EditorTaskType, NoneType], required=False, default=None, alias='editorTaskType', alias_priority=1, frozen=True), 'id': FieldInfo(annotation=str, required=True, alias='id', alias_priority=1, frozen=True), 'media_type': FieldInfo(annotation=Union[MediaType, NoneType], required=False, default=None, alias='mediaType', alias_priority=1, frozen=True), 'name': FieldInfo(annotation=str, required=True, alias='name', alias_priority=1, frozen=True), 'status': FieldInfo(annotation=Union[LabelingServiceStatus, NoneType], required=False, default=None, alias='status', alias_priority=1, frozen=True), 'tags': FieldInfo(annotation=Union[List[labelbox.schema.labeling_service_dashboard.LabelingServiceDashboardTags], NoneType], required=False, default=None, alias='tags', alias_priority=1, frozen=True), 'tasks_completed_count': FieldInfo(annotation=int, required=True, alias='tasksCompletedCount', alias_priority=1, frozen=True), 'tasks_remaining_count': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, alias='tasksRemainingCount', alias_priority=1, frozen=True), 'updated_at': FieldInfo(annotation=Union[datetime, NoneType], required=False, default=None, alias='updatedAt', alias_priority=1, frozen=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

property service_type

Descriptive labeling service definition by media type and editor task type

class labelbox.schema.labeling_service_dashboard.LabelingServiceDashboardTags(*, id: str, text: str, color: str, type: str)[source]

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'color': FieldInfo(annotation=str, required=True), 'id': FieldInfo(annotation=str, required=True), 'text': FieldInfo(annotation=str, required=True), 'type': FieldInfo(annotation=str, required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.