RasterioSourceConfig#

Note

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

pydantic model RasterioSourceConfig[source]#

Configure a RasterioSource.

Show JSON schema

{
   "title": "RasterioSourceConfig",
   "description": "Configure a :class:`.RasterioSource`.",
   "type": "object",
   "properties": {
      "channel_order": {
         "title": "Channel Order",
         "description": "The sequence of channel indices to use when reading imagery.",
         "type": "array",
         "items": {
            "type": "integer"
         }
      },
      "transformers": {
         "title": "Transformers",
         "default": [],
         "type": "array",
         "items": {
            "$ref": "#/definitions/RasterTransformerConfig"
         }
      },
      "bbox": {
         "title": "Bbox",
         "description": "User-specified bbox in pixel coords in the form (ymin, xmin, ymax, xmax). Useful for cropping the raster source so that only part of the raster is read from.",
         "type": "array",
         "minItems": 4,
         "maxItems": 4,
         "items": [
            {
               "type": "integer"
            },
            {
               "type": "integer"
            },
            {
               "type": "integer"
            },
            {
               "type": "integer"
            }
         ]
      },
      "type_hint": {
         "title": "Type Hint",
         "default": "rasterio_source",
         "enum": [
            "rasterio_source"
         ],
         "type": "string"
      },
      "uris": {
         "title": "Uris",
         "description": "One or more image URIs that comprise the imagery for a scene. The format of each file can be any that can be read by Rasterio/GDAL. If > 1 URI is provided, a VRT will be created to mosaic together the individual images.",
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "array",
               "items": {
                  "type": "string"
               }
            }
         ]
      },
      "allow_streaming": {
         "title": "Allow Streaming",
         "description": "Stream assets as needed rather than downloading them.",
         "default": false,
         "type": "boolean"
      }
   },
   "required": [
      "uris"
   ],
   "additionalProperties": false,
   "definitions": {
      "RasterTransformerConfig": {
         "title": "RasterTransformerConfig",
         "description": "Configure a :class:`.RasterTransformer`.",
         "type": "object",
         "properties": {
            "type_hint": {
               "title": "Type Hint",
               "default": "raster_transformer",
               "enum": [
                  "raster_transformer"
               ],
               "type": "string"
            }
         },
         "additionalProperties": false
      }
   }
}

Config

extra: str = forbid
validate_assignment: bool = True

Fields

allow_streaming (bool)
bbox (Optional[Tuple[int, int, int, int]])
channel_order (Optional[List[int]])
transformers (List[rastervision.core.data.raster_transformer.raster_transformer_config.RasterTransformerConfig])
type_hint (Literal['rasterio_source'])
uris (Union[str, List[str]])

field allow_streaming: bool = False#: Stream assets as needed rather than downloading them.

field bbox: Optional[Tuple[int, int, int, int]] = None#: User-specified bbox in pixel coords in the form (ymin, xmin, ymax, xmax). Useful for cropping the raster source so that only part of the raster is read from.

field channel_order: Optional[List[int]] = None#: The sequence of channel indices to use when reading imagery.

field transformers: List[RasterTransformerConfig] = []#

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

field uris: Union[str, List[str]] [Required]#: One or more image URIs that comprise the imagery for a scene. The format of each file can be any that can be read by Rasterio/GDAL. If > 1 URI is provided, a VRT will be created to mosaic together the individual images.

build(tmp_dir, use_transformers=True)[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.

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().

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: Optional[RVPipelineConfig] = None, scene: Optional[SceneConfig] = 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 (Optional[RVPipelineConfig]) –
scene (Optional[SceneConfig]) –

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