ChipClassificationLabelSource#

class ChipClassificationLabelSource[source]#

Bases: LabelSource

A source of chip classification labels.

Ideally the vector_source contains a square for each cell in the grid. But in reality, it can be difficult to label imagery in such an exhaustive way. So, this can also handle sources with non-overlapping polygons that do not necessarily cover the entire extent. It infers the grid of cells and associated class_ids using the extent and options if infer_cells is set to True.

Attributes

extent

__init__(label_source_config: ChipClassificationLabelSourceConfig, vector_source: VectorSource, extent: Box = None, lazy: bool = False)[source]#

Constructs a LabelSource for chip classification.

Parameters

label_source_config (ChipClassificationLabelSourceConfig) – Config for class inference.
vector_source (VectorSource) – Source of vector labels.
extent (Box) – Box used to filter the labels by extent or compute grid.
lazy (bool, optional) – If True, labels are not populated during initialization. Defaults to False.

Methods

`__init__`(label_source_config, vector_source)	Constructs a LabelSource for chip classification.
`get_labels`([window])	Return labels overlapping with window.
`infer_cells`([cells])	Infer labels for a list of cells.
`populate_labels`([cells])	Populate self.labels by either reading or inferring.
`validate_labels`(df)

__init__(label_source_config: ChipClassificationLabelSourceConfig, vector_source: VectorSource, extent: Box = None, lazy: bool = False)[source]#

Constructs a LabelSource for chip classification.

Parameters

label_source_config (ChipClassificationLabelSourceConfig) – Config for class inference.
vector_source (VectorSource) – Source of vector labels.
extent (Box) – Box used to filter the labels by extent or compute grid.
lazy (bool, optional) – If True, labels are not populated during initialization. Defaults to False.

get_labels(window: Optional[Box] = None) → ChipClassificationLabels[source]#

Return labels overlapping with window.

Parameters

window (Optional[Box]) – Box

Returns

Labels overlapping with window. If window is None,: returns all labels.

Return type

ChipClassificationLabels

infer_cells(cells: Optional[Iterable[Box]] = None) → ChipClassificationLabels[source]#

Infer labels for a list of cells. Only cells whose labels are not already known are inferred.

Parameters: cells (Optional[Iterable[Box]], optional) – Cells whose labels are to be inferred. Defaults to None.
Returns: labels
Return type: ChipClassificationLabels

populate_labels(cells: Optional[Iterable[Box]] = None) → None[source]#

Populate self.labels by either reading or inferring.

If cfg.infer_cells is True or specific cells are given, the labels are inferred. Otherwise, they are read from the geojson.

Parameters: cells (Optional[Iterable[Box]]) –
Return type: None

validate_labels(df: geopandas.GeoDataFrame) → None[source]#

Parameters: df (geopandas.GeoDataFrame) –
Return type: None

property extent: Box#