BufferTransformerConfig#

Note

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

pydantic model BufferTransformerConfig[source]#

Configure a BufferTransformer.

This is useful, for example, for buffering lines representing roads so that their width roughly matches the width of roads in the imagery.

Show JSON schema

{
   "title": "BufferTransformerConfig",
   "description": "Configure a :class:`.BufferTransformer`.\n\nThis is useful, for example, for buffering lines representing roads so that\ntheir width roughly matches the width of roads in the imagery.",
   "type": "object",
   "properties": {
      "type_hint": {
         "const": "buffer_transformer",
         "default": "buffer_transformer",
         "enum": [
            "buffer_transformer"
         ],
         "title": "Type Hint",
         "type": "string"
      },
      "geom_type": {
         "description": "The geometry type to apply this transform to. E.g. \"LineString\", \"Point\", \"Polygon\".",
         "title": "Geom Type",
         "type": "string"
      },
      "class_bufs": {
         "additionalProperties": {
            "anyOf": [
               {
                  "type": "number"
               },
               {
                  "type": "null"
               }
            ]
         },
         "default": {},
         "description": "Mapping from class IDs to buffer amounts (in pixels). If a class ID is not found in the mapping, the value specified by the default_buf field will be used. If the buffer value for a class is None, then no buffering will be applied to the geoms of that class and the geom won't get converted to a Polygon. Not converting to Polygon is incompatible with the currently available LabelSources, but may be useful in the future.",
         "title": "Class Bufs",
         "type": "object"
      },
      "default_buf": {
         "anyOf": [
            {
               "type": "number"
            },
            {
               "type": "null"
            }
         ],
         "default": 1,
         "description": "Default buffer to apply to classes not in class_bufs. If None, no buffering will be applied to the geoms of those classes.",
         "title": "Default Buf"
      }
   },
   "additionalProperties": false,
   "required": [
      "geom_type"
   ]
}

Config:

extra: str = forbid
validate_assignment: bool = True

Fields:

class_bufs (dict[int, float | None])
default_buf (float | None)
geom_type (str)
type_hint (Literal['buffer_transformer'])

field class_bufs: dict[int, float | None] = {}#: Mapping from class IDs to buffer amounts (in pixels). If a class ID is not found in the mapping, the value specified by the default_buf field will be used. If the buffer value for a class is None, then no buffering will be applied to the geoms of that class and the geom won’t get converted to a Polygon. Not converting to Polygon is incompatible with the currently available LabelSources, but may be useful in the future.

field default_buf: float | None = 1#: Default buffer to apply to classes not in class_bufs. If None, no buffering will be applied to the geoms of those classes.

field geom_type: str [Required]#: The geometry type to apply this transform to. E.g. “LineString”, “Point”, “Polygon”.

field type_hint: Literal['buffer_transformer'] = 'buffer_transformer'#

build(class_config: ClassConfig | None = None) → BufferTransformer[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.

Parameters:: class_config (ClassConfig | None) –
Return type:: BufferTransformer

classmethod deserialize(inp: str | dict | Config) → Self#

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

If inp is already a Config, it is returned as is.

Parameters:: inp (str | dict | Config) – a URI to a JSON file or a dict.
Return type:: Self

classmethod from_dict(cfg_dict: dict) → Self#

Deserialize Config from a dict.

Parameters:: cfg_dict (dict) – Dict to deserialize.
Return type:: Self

classmethod from_file(uri: str) → Self#

Deserialize Config from a JSON file, upgrading if possible.

Parameters:: uri (str) – URI to load from.
Return type:: Self

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().

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: RVPipelineConfig | None = None, scene: SceneConfig | None = None) → None#

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.

Parameters:

pipeline (RVPipelineConfig | None) –
scene (SceneConfig | None) –

Return type:

None

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