def get_ancestors_by_prediction(
label_schema: LabelSchemaEntity, prediction: ScoredLabel
) -> List[ScoredLabel]:
"""
Get all the ancestors for a given label node
"""
ancestor_labels = label_schema.get_ancestors(prediction.get_label())
return [ScoredLabel(al, prediction.probability) for al in ancestor_labels]
def test_scored_label(self):
"""
<b>Description:</b>
Check the ScoredLabel can correctly return the value
<b>Input data:</b>
LabelEntity
<b>Expected results:</b>
Test passes if the results match
"""
car = LabelEntity(id=ID(123456789),
name="car",
domain=Domain.DETECTION,
is_empty=True)
person = LabelEntity(id=ID(987654321),
name="person",
domain=Domain.DETECTION,
is_empty=True)
car_label = ScoredLabel(car)
person_label = ScoredLabel(person)
for attr in [
"id", "name", "color", "hotkey", "creation_date", "is_empty"
]:
assert getattr(car_label, attr) == getattr(car, attr)
assert car_label.get_label() == car
assert car_label == ScoredLabel(car)
assert car_label != car
assert car_label != person_label
assert hash(car_label) == hash(str(car_label))
probability = 0.0
assert car_label.probability == probability
delta_probability = 0.4
probability += delta_probability
car_label.probability += delta_probability
assert car_label.probability == probability
car.color = Color(red=16, green=15, blue=56, alpha=255)
assert (
"ScoredLabel(123456789, name=car, probability=0.4, domain=DETECTION, color="
in repr(car_label))
assert "Color(red=16, green=15, blue=56, alpha=255), hotkey=ctrl+0)" in repr(
car_label)