aws.osml.gdal.gdal_utils module
- aws.osml.gdal.gdal_utils.load_gdal_dataset(image_path: str) Tuple[Dataset, SensorModel | None][source]
This function loads a GDAL raster dataset from the path provided and constructs a camera model abstraction used to georeference locations on this image.
- Parameters:
image_path – the path to the raster data, may be a local path or a virtual file system (e.g. /vsis3/…)
- Returns:
the raster dataset and sensor model
- aws.osml.gdal.gdal_utils.get_minmax_for_type(gdal_type: int) Tuple[float, float][source]
This function computes the minimum and maximum values that can be stored in a given GDAL pixel type.
- Parameters:
gdal_type – the pixel type
- Returns:
tuple of min, max values
- aws.osml.gdal.gdal_utils.get_type_and_scales(raster_dataset: Dataset, desired_output_type: int | None = None, range_adjustment: RangeAdjustmentType = RangeAdjustmentType.NONE) Tuple[int, List[List[int]]][source]
Get type and scales of a provided raster dataset
- Parameters:
raster_dataset – the raster dataset containing the region
desired_output_type – type to be output after dynamic range adjustments
range_adjustment – the type of pixel scaling effort to
- Returns:
a tuple containing type and scales
- aws.osml.gdal.gdal_utils.get_image_extension(image_path: str) str[source]
Get the image extension based on the provided image path
- Parameters:
image_path – an image path
- Returns:
image extension
- aws.osml.gdal.gdal_utils.select_extension(image_path: str, possible_extensions: List[str]) str[source]
Check to see if provided image path contains a known possible extensions
- Parameters:
image_path – an image path
possible_extensions – list of possible extensions
- Returns:
select extension
- aws.osml.gdal.gdal_utils.normalize_extension(unnormalized_extension: str) str[source]
Convert the extension into a proper formatted string
- Parameters:
unnormalized_extension – an unnormalized extension
- Returns:
normalized extension