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visual_critical_discourse_a…/shared/mongodb/classes/model_data.py
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"""Definition of ModelData data model."""
from __future__ import annotations
from .angle import AngleData
from .contact import ContactData
from .data_model import DataModel
from .distance import DistanceData
from .framing import FramingData
from .information_value import InformationValueData
from .modality_color import ModalityColorData
from .modality_depth import ModalityDepthData
from .modality_lighting import ModalityLightingData
from .point_of_view import PointOfViewData
from .salience import SalienceData
from .visual_syntax import VisualSyntaxData
class ModelData(DataModel):
"""ModelData model for data IO with combined ML model."""
visual_syntax: VisualSyntaxData
contact: ContactData
angle: AngleData
point_of_view: PointOfViewData
distance: DistanceData
modality_lighting: ModalityLightingData
modality_color: ModalityColorData
modality_depth: ModalityDepthData
information_value: InformationValueData
framing: FramingData
salience: SalienceData
@classmethod
def from_random(cls) -> ModelData:
"""Instantiate with random numbers."""
kwargs = {
field: field_info.annotation.from_random() # type: ignore
for field, field_info in cls.model_fields.items()
}
return cls(**kwargs)
@classmethod
def from_prediction_dict(
cls,
prediction_dict: dict,
) -> ModelData:
"""Instantiate from prediction dictionary."""
kwargs = {
'visual_syntax': VisualSyntaxData.from_tensor(
prediction_dict['visual_syntax'],
),
'contact': ContactData.from_tensor(
prediction_dict['contact'],
),
'angle': AngleData.from_tensor(
prediction_dict['angle'],
),
'point_of_view': PointOfViewData.from_tensor(
prediction_dict['point_of_view'],
),
'distance': DistanceData.from_tensor(
prediction_dict['distance'],
),
'modality_lighting': ModalityLightingData.from_tensor(
prediction_dict['modality_lighting'],
),
'modality_color': ModalityColorData.from_tensor(
prediction_dict['modality_color'],
),
'modality_depth': ModalityDepthData.from_tensor(
prediction_dict['modality_depth'],
),
'information_value': InformationValueData.from_tensor(
prediction_dict['information_value'],
),
'framing': FramingData.from_tensor(
prediction_dict['framing'],
),
'salience': SalienceData.from_tensor(
prediction_dict['salience'],
),
}
return cls(**kwargs)
@classmethod
def from_annotations(
cls,
visual_syntax: str,
contact: str,
angle: str,
point_of_view: str,
distance: str,
modality_lighting: str,
modality_color: str,
modality_depth: str,
information_value: str,
framing: str,
salience: str,
) -> ModelData:
"""Instantiate from annotation."""
kwargs = {
'visual_syntax': VisualSyntaxData.from_choice(visual_syntax),
'contact': ContactData.from_choice(contact),
'angle': AngleData.from_choice(angle),
'point_of_view': PointOfViewData.from_choice(point_of_view),
'distance': DistanceData.from_choice(distance),
'modality_lighting': ModalityLightingData.from_choice(modality_lighting),
'modality_color': ModalityColorData.from_choice(modality_color),
'modality_depth': ModalityDepthData.from_choice(modality_depth),
'information_value': InformationValueData.from_choice(information_value),
'framing': FramingData.from_choice(framing),
'salience': SalienceData.from_choice(salience),
}
return cls(**kwargs)