Source code for rastervision.core.data.vector_transformer.class_inference_transformer_config

from typing import TYPE_CHECKING, Dict, Optional

from rastervision.pipeline.config import register_config, Field
from rastervision.core.data.vector_transformer import (
    VectorTransformerConfig, ClassInferenceTransformer)

if TYPE_CHECKING:
    from rastervision.core.data import ClassConfig


[docs]@register_config('class_inference_transformer') class ClassInferenceTransformerConfig(VectorTransformerConfig): """Configure a :class:`.ClassInferenceTransformer`.""" default_class_id: Optional[int] = Field( None, description='The default ``class_id`` to use if class cannot be ' 'inferred using other mechanisms. If a feature has an inferred ' '``class_id`` of ``None``, then it will be deleted. ' 'Defaults to ``None``.') class_id_to_filter: Optional[Dict[int, list]] = Field( None, description='Map from ``class_id`` to JSON filter used to infer ' 'missing class IDs. Each key should be a class ID, and its value ' 'should be a boolean expression which is run against the property ' 'field for each feature. This allows matching different features to ' 'different class IDs based on its properties. The expression schema ' 'is that described by ' 'https://docs.mapbox.com/mapbox-gl-js/style-spec/other/#other-filter. ' 'Defaults to ``None``.') class_name_mapping: dict[str, str] = Field( None, description='``old_name --> new_name`` mapping for values in the ' '``class_name`` or ``label`` property of the GeoJSON features. The ' '``new_name`` must be a valid class name in the ``ClassConfig``. This ' 'can also be used to merge multiple classes into one e.g.: ' '``dict(car="vehicle", truck="vehicle")``. Defaults to None.')
[docs] def build(self, class_config: Optional['ClassConfig'] = None ) -> ClassInferenceTransformer: return ClassInferenceTransformer( self.default_class_id, class_config=class_config, class_id_to_filter=self.class_id_to_filter, class_name_mapping=self.class_name_mapping)