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LabelRow Objects

class LabelRow(base_orm.BaseORM)
A label row contains a data unit or a collection of data units and associated labels, and is specific to a data asset with type video or img_group:
  • A label row with a data asset of type video contains a single data unit.
  • A label row with a data asset of type img_group contains any number of data units.
The label row ORM is as follows:
  • label_hash (uid) is the unique identifier of the label row
  • dataset_hash (uid) is the unique identifier of the dataset which contains the particular video or image group
  • dataset_title is the title of the dataset which contains the particular video or image group
  • data_title is the title of the video or image group
  • data_type either video or img_group depending on data type
  • data_units a dictionary with (key: data hash, value: data unit) pairs.
  • object_answers is a dictionary with (key: object hash, value: object answer) pairs.
  • classification_answers is a dictionary with (key: classification hash, value: classification answer) pairs.
  • object_actions is a dictionary with (key: <object_hash>, value: object action) pairs.
  • label_status is a string indicating label status. It can take the values enumerated in LabelStatus. Note that this does not reflect the status shown in the Projects->Labels section on the web-app.
A data unit, mentioned for the dictionary entry data_units above, has in the form:: 
    label_row = {  # The label row
        # ...
        "data_units": {
            "<data_hash>": {
                "data_hash": "<data_hash>",  # A data_hash (uid) string
                "data_title": "A data title",
                "data_link": "<data_link>",  # Signed URL that expiring after 7 days
                "data_type": "<data_type>",  # (video/mp4, image/jpeg, etc.)
                "data_fps": 24.95,           # For video, the frame rate
                "data_sequence": "0",        # Defines order of data units
                "width": 640,                # The width of the content
                "height": 610,               # The height of the content
                "labels": {
                    # ...
                }
            },
            # ...,
        }
    }
A data unit can have any number of vector labels (e.g. bounding box, polygon, keypoint) and classifications. Objects and classifications A data unit can have any number of vector labels (e.g., bounding boxes, polygons, polylines, keypoints) and classifications. Each frame-level object and classification has unique identifiers ‘objectHash’ and ‘classificationHash’. Each frame-level entity has a unique feature identifier ‘featureHash’, defined in the editor ontology. The object and classification answers are contained separately from the individual data units to preserve space for video, sequential images, DICOM, etc. The objects and classifications answer dictionaries contain classification ‘answers’ (i.e. attributes that describe the object or classification). This is to avoid storing the information at every frame in the blurb, of particular importance for videos. A labels dictionary for video is in the form:: 
    label_row["data_units"]["<data_hash>"]["labels"] = {
        "<frame_number>": {
            "objects": [
                # { object 1 },
                # { object 2 },
                # ...
            ],
            "classifications": [
                # { classification 1 },
                # { classification 2 },
                # ...
            ],
        }
    }
A labels dictionary for an img_group data unit is in the form:: 
    label_row["data_units"]["<data_hash>"]["labels"] = {
        "objects": [
            # { object 1 },
            # { object 2 },
            # ...
        ],
        "classifications": [
            # { classification 1 },
            # { classification 2 },
            # ...
        ],
    }
The object answers dictionary is in the form:: 
    label_row["object_answers"] = {
        "<object_hash>": {
            "objectHash": "<object_hash>",
            "classifications": [
                # {answer 1},
                # {answer 2},
                # ...
            ]
        },
        # ...
    }
The classification answers dictionary is in the form:: 
    label_row["classification_answers"] = {
        "<classification_hash>": {
            "classificationHash": "<classification_hash>",
            "classifications": [
                # {answer 1},
                # {answer 2},
                # ...
            ],
        },
        # ...
    }
The object actions dictionary is in the form:: 
    label_row["object_actions"] = {
        "<object_hash>": {
            "objectHash": "<object_hash>",
            "actions": [
                # {answer 1},
                # {answer 2},
                # ...
            ],
        },
        # ...
    }

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AnnotationTaskStatus Objects

class AnnotationTaskStatus(Enum)
Status of an annotation task in a project workflow. Values:
  • QUEUED: The task has been created and is waiting to be assigned.
  • ASSIGNED: The task has been assigned to an annotator but work has not necessarily started yet.
  • IN_REVIEW: The task has been completed by the annotator and is currently in review.
  • RETURNED: The reviewer has returned the task to the annotator for changes.
  • COMPLETED: The task has been completed and no further action is required.

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ShadowDataState Objects

class ShadowDataState(Enum)
Specifies the kind of data to fetch when working with a BenchmarkQa project

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ALL_DATA

Fetch all the label rows

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SHADOW_DATA

Only fetch the label rows that were submitted against “shadow data”: the annotator’s view of the benchmark

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NOT_SHADOW_DATA

Only fetch the label rows for “production” data

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LabelStatus Objects

class LabelStatus(Enum)

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MISSING_LABEL_STATUS

This value will be displayed if the Encord platform has a new label status and your SDK version does not understand it yet. Please update your SDK to the latest version.

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WorkflowGraphNode Objects

@dataclass(frozen=True)
class WorkflowGraphNode()
Lightweight representation of a workflow graph node. Arguments:
  • uuid - UUID of the workflow stage as a string.
  • title - Human-readable title of the workflow stage.

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LabelRowMetadata Objects

@dataclass(frozen=True)
class LabelRowMetadata(Formatter)
Contains helpful information about a label row.

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label_hash

Only present if the label row is initiated

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created_at

Only present if the label row is initiated

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last_edited_at

Only present if the label row is initiated

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branch_name

Only present if the label row is initiated or branch_name is set specifically

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data_hash

Only present if the label row is for a child element of a group Can be None for label rows of image groups or DICOM series.

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label_status

Can be None for TMS2 projects

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annotation_task_status

Only available for TMS2 project

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is_shadow_data

Only available for the VIDEO and AUDIO data_type

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duration

Only available for the VIDEO data_type

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width

Only available for the AUDIO data_type

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priority

Only available for not complete tasks

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file_type

Only available for certain read requests

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to_dict

def to_dict() -> Dict
Returns: The dict equivalent of LabelRowMetadata.

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LabelValidationState Objects

class LabelValidationState(BaseDTO)
Result of validating a label row. Arguments:
  • label_hash - Identifier of the label row that was validated.
  • branch_name - Name of the branch on which the label row resides.
  • version - Version number of the label row that was validated.
  • is_valid - True if the label row is considered valid, otherwise False.
  • errors - List of validation error messages, if any.

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WorkflowGraphNodeDTO Objects

class WorkflowGraphNodeDTO(BaseDTO)
Data transfer object representing a workflow graph node. Arguments:
  • uuid - UUID of the workflow stage as a string.
  • title - Human-readable title of the workflow stage.

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LabelRowMetadataDTO Objects

class LabelRowMetadataDTO(BaseDTO)
Contains helpful information about a label row.

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label_hash

Only present if the label row is initiated

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created_at

Only present if the label row is initiated

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last_edited_at

Only present if the label row is initiated

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branch_name

Only present if the label row is initiated or branch_name is set specifically Can be None for label rows of image groups or DICOM series.

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label_status

Can be None for TMS2 projects

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annotation_task_status

Only available for TMS2 project

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is_shadow_data

Only available for the VIDEO and AUDIO data_type

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duration

Only available for the VIDEO data_type

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width

Only available for the AUDIO data_type

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priority

Only available for not complete tasks

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file_type

Only available for certain read requests

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label_row_metadata_dto_to_label_row_metadata

def label_row_metadata_dto_to_label_row_metadata(
        label_row_metadata_dto: LabelRowMetadataDTO) -> LabelRowMetadata
Convert a LabelRowMetadataDTO instance to a LabelRowMetadata dataclass. This helper is useful when working with DTOs returned by the API but you prefer the richer, formatter-enabled LabelRowMetadata representation in your application code. Arguments:
  • label_row_metadata_dto - Metadata DTO returned from the API.
Returns:
  • LabelRowMetadata - Equivalent dataclass instance with the same fields populated.