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)