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": {
         "anyOf": [
            {
               "items": {
                  "type": "integer"
               },
               "type": "array"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "description": "The sequence of channel indices to use when reading imagery.",
         "title": "Channel Order"
      },
      "transformers": {
         "default": [],
         "items": {
            "$ref": "#/$defs/RasterTransformerConfig"
         },
         "title": "Transformers",
         "type": "array"
      },
      "bbox": {
         "anyOf": [
            {
               "maxItems": 4,
               "minItems": 4,
               "prefixItems": [
                  {
                     "type": "integer"
                  },
                  {
                     "type": "integer"
                  },
                  {
                     "type": "integer"
                  },
                  {
                     "type": "integer"
                  }
               ],
               "type": "array"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "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.",
         "title": "Bbox"
      },
      "type_hint": {
         "const": "rasterio_source",
         "default": "rasterio_source",
         "enum": [
            "rasterio_source"
         ],
         "title": "Type Hint",
         "type": "string"
      },
      "uris": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "items": {
                  "type": "string"
               },
               "type": "array"
            }
         ],
         "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.",
         "title": "Uris"
      },
      "allow_streaming": {
         "default": false,
         "description": "Stream assets as needed rather than downloading them.",
         "title": "Allow Streaming",
         "type": "boolean"
      }
   },
   "$defs": {
      "RasterTransformerConfig": {
         "additionalProperties": false,
         "description": "Configure a :class:`.RasterTransformer`.",
         "properties": {
            "type_hint": {
               "const": "raster_transformer",
               "default": "raster_transformer",
               "enum": [
                  "raster_transformer"
               ],
               "title": "Type Hint",
               "type": "string"
            }
         },
         "title": "RasterTransformerConfig",
         "type": "object"
      }
   },
   "additionalProperties": false,
   "required": [
      "uris"
   ]
}

Config:
  • extra: str = forbid

  • validate_assignment: bool = True

Fields:
field allow_streaming: bool = False#

Stream assets as needed rather than downloading them.

field bbox: tuple[int, int, int, int] | None = 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: list[int] | None = 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: 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: str | None, use_transformers: bool = True) RasterioSource[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:
  • tmp_dir (str | None) –

  • use_transformers (bool) –

Return type:

RasterioSource

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:
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