Objects.classification instance

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ClassificationInstance Objects

class ClassificationInstance()

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classification_hash

@property
def classification_hash() -> str

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classification_name

@property
def classification_name() -> str

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feature_hash

@property
def feature_hash() -> str

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created_by

@created_by.setter
def created_by(created_by: Optional[str]) -> None

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last_edited_by

@last_edited_by.setter
def last_edited_by(last_edited_by: Optional[str]) -> None

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set_for_frames

def set_for_frames(frames: Frames = 0,
                   *,
                   overwrite: bool = False,
                   created_at: Optional[datetime] = None,
                   created_by: Optional[str] = None,
                   confidence: float = DEFAULT_CONFIDENCE,
                   manual_annotation: bool = DEFAULT_MANUAL_ANNOTATION,
                   last_edited_at: Optional[datetime] = None,
                   last_edited_by: Optional[str] = None,
                   reviews: Optional[List[dict]] = None) -> None

• frames - The frame to add the classification instance to. Defaulting to the first frame for convenience.
• overwrite - If True, overwrite existing data for the given frames. This will not reset all the non-specified values. If False and data already exists for the given frames, raises an error.
• created_at - Optionally specify the creation time of the classification instance on this frame. Defaults to datetime.now().
• created_by - Optionally specify the creator of the classification instance on this frame. Defaults to the current SDK user.
• last_edited_at - Optionally specify the last edit time of the classification instance on this frame. Defaults to datetime.now().
• last_edited_by - Optionally specify the last editor of the classification instance on this frame. Defaults to the current SDK user.
• confidence - Optionally specify the confidence of the classification instance on this frame. Defaults to 1.0.
• manual_annotation - Optionally specify whether the classification instance on this frame was manually annotated. Defaults to True.
• reviews - Should only be set by internal functions.

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get_annotation

def get_annotation(frame: Union[int, str] = 0) -> Annotation

• frame - Either the frame number or the image hash if the data type is an image or image group. Defaults to the first frame.

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get_annotations

def get_annotations(
) -> Union[List[Annotation], List[_ClassificationAnnotation]]

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set_answer

def set_answer(answer: Union[str, NumericAnswerValue, Option,
                             Sequence[Option]],
               attribute: Optional[Attribute] = None,
               overwrite: bool = False) -> None

• answer - The answer to set.
• attribute - The ontology attribute to set the answer for. If not set, this will be attempted to be inferred. For answers to RadioAttribute or ChecklistAttribute, this can be inferred automatically. For TextAttribute, this will only be inferred if there is only one possible TextAttribute to set for the entire classification instance. Otherwise, a LabelRowError will be thrown.
• overwrite - If True, the answer will be overwritten if it already exists. If False, this will throw a LabelRowError if the answer already exists.

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set_answer_from_list

def set_answer_from_list(answers_list: List[AttributeDict]) -> None

• answers_list - The list to set the answer from.

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get_answer

def get_answer(
    attribute: Optional[Attribute] = None
) -> Union[str, Option, Iterable[Option], None]

• attribute - The ontology attribute to get the answer for.

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delete_answer

def delete_answer(attribute: Optional[Attribute] = None) -> None

• attribute - The ontology attribute to delete the answer for. If not provided, the first level attribute is used.

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copy

def copy() -> ClassificationInstance

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get_all_static_answers

def get_all_static_answers() -> List[Answer]

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Annotation Objects

class Annotation(_ClassificationAnnotation)

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reviews

@property
def reviews() -> Optional[List[dict]]