ObjectDetectionLabelSourceConfig#

Note

All Configs are derived from rastervision.pipeline.config.Config, which itself is a pydantic Model.

pydantic model ObjectDetectionLabelSourceConfig[source]#

Configure an ObjectDetectionLabelSource.

Show JSON schema
{
   "title": "ObjectDetectionLabelSourceConfig",
   "description": "Configure an :class:`.ObjectDetectionLabelSource`.",
   "type": "object",
   "properties": {
      "type_hint": {
         "title": "Type Hint",
         "default": "object_detection_label_source",
         "enum": [
            "object_detection_label_source"
         ],
         "type": "string"
      },
      "vector_source": {
         "$ref": "#/definitions/VectorSourceConfig"
      }
   },
   "required": [
      "vector_source"
   ],
   "additionalProperties": false,
   "definitions": {
      "VectorTransformerConfig": {
         "title": "VectorTransformerConfig",
         "description": "Configure a :class:`.VectorTransformer`.",
         "type": "object",
         "properties": {
            "type_hint": {
               "title": "Type Hint",
               "default": "vector_transformer",
               "enum": [
                  "vector_transformer"
               ],
               "type": "string"
            }
         },
         "additionalProperties": false
      },
      "VectorSourceConfig": {
         "title": "VectorSourceConfig",
         "description": "Configure a :class:`.VectorSource`.",
         "type": "object",
         "properties": {
            "transformers": {
               "title": "Transformers",
               "description": "List of VectorTransformers.",
               "default": [],
               "type": "array",
               "items": {
                  "$ref": "#/definitions/VectorTransformerConfig"
               }
            },
            "type_hint": {
               "title": "Type Hint",
               "default": "vector_source",
               "enum": [
                  "vector_source"
               ],
               "type": "string"
            }
         },
         "additionalProperties": false
      }
   }
}

Config
  • extra: str = forbid

  • validate_assignment: bool = True

Fields
Validators
field type_hint: Literal['object_detection_label_source'] = 'object_detection_label_source'#
field vector_source: VectorSourceConfig [Required]#
Validated by
build(class_config, crs_transformer, bbox, tmp_dir=None) ObjectDetectionLabelSource[source]#

Build an instance of the corresponding type of object using this config.

For example, BackendConfig will build a Backend object. The arguments to this method will vary depending on the type of Config.

Return type

ObjectDetectionLabelSource

validator ensure_required_transformers  »  vector_source[source]#

Add class-inference and buffer transformers if absent.

Parameters

v (VectorSourceConfig) –

Return type

VectorSourceConfig

classmethod from_file(uri: str) Config#

Deserialize a Config from a JSON file, upgrading if possible.

Parameters

uri (str) – URI to load from.

Return type

Config

recursive_validate_config()#

Recursively validate hierarchies of Configs.

This uses reflection to call validate_config on a hierarchy of Configs using a depth-first pre-order traversal.

revalidate()#

Re-validate an instantiated Config.

Runs all Pydantic validators plus self.validate_config().

Adapted from: https://github.com/samuelcolvin/pydantic/issues/1864#issuecomment-679044432

to_file(uri: str, with_rv_metadata: bool = True) None#

Save a Config to a JSON file, optionally with RV metadata.

Parameters
  • uri (str) – URI to save to.

  • with_rv_metadata (bool) – If True, inject Raster Vision metadata such as plugin_versions, so that the config can be upgraded when loaded.

Return type

None

update(pipeline=None, scene=None)[source]#

Update any fields before validation.

Subclasses should override this to provide complex default behavior, for example, setting default values as a function of the values of other fields. The arguments to this method will vary depending on the type of Config.

validate_config()#

Validate fields that should be checked after update is called.

This is to complement the builtin validation that Pydantic performs at the time of object construction.

validate_list(field: str, valid_options: List[str])#

Validate a list field.

Parameters
  • field (str) – name of field to validate

  • valid_options (List[str]) – values that field is allowed to take

Raises

ConfigError – if field is invalid