ChipClassificationLabels#

class ChipClassificationLabels[source]#

Bases: Labels

Represents a spatial grid of cells associated with classes.

__init__(cell_to_label: Optional[Dict[Box, Tuple[int, Optional[Sequence[float]]]]] = None)[source]#

Parameters: cell_to_label (Optional[Dict[Box, Tuple[int, Optional[Sequence[float]]]]]) –

Methods

`__init__`([cell_to_label])
`extend`(labels)	Adds cells contained in labels.
`filter_by_aoi`(aoi_polygons)	Return a copy of these labels filtered by given AOI polygons.
`from_predictions`(windows, predictions)	Overrid to convert predictions to (class_id, scores) pairs.
`get_cell_class_id`(cell)	Return class_id for a cell.
`get_cell_scores`(cell)	Return scores for a cell.
`get_cells`()	Return list of all cells (list of Box).
`get_class_ids`()	Return list of class_ids for all cells.
`get_scores`()	Return list of scores for all cells.
`get_singleton_labels`(cell)	Return Labels object representing a single cell.
`get_values`()	Return list of class_ids and scores for all cells.
`make_empty`()	Instantiate an empty instance of this class.
`save`(uri, class_config, crs_transformer)	Save labels as a GeoJSON file.
`set_cell`(cell, class_id[, scores])	Set cell and its class_id.

__add__(other: ChipClassificationLabels) → ChipClassificationLabels[source]#

Add labels to these labels.

Returns a concatenation of this and the other labels.

Parameters: other (ChipClassificationLabels) –
Return type: ChipClassificationLabels

__contains__(cell: Box) → bool[source]#

Parameters: cell (Box) –
Return type: bool

__getitem__(cell: Box) → ClassificationLabel[source]#

Parameters: cell (Box) –
Return type: ClassificationLabel

__init__(cell_to_label: Optional[Dict[Box, Tuple[int, Optional[Sequence[float]]]]] = None)[source]#

Parameters: cell_to_label (Optional[Dict[Box, Tuple[int, Optional[Sequence[float]]]]]) –

__setitem__(window: Box, value: Tuple[int, Optional[Sequence[float]]])[source]#

Parameters

window (Box) –
value (Tuple[int, Optional[Sequence[float]]]) –

extend(labels: ChipClassificationLabels) → None[source]#

Adds cells contained in labels.

Parameters: labels (ChipClassificationLabels) – ChipClassificationLabels
Return type: None

filter_by_aoi(aoi_polygons: Iterable[Polygon])[source]#

Return a copy of these labels filtered by given AOI polygons.

Parameters: aoi_polygons (Iterable[Polygon]) – List of AOI polygons to filter by, in pixel coordinates.

classmethod from_predictions(windows: Iterable[Box], predictions: Iterable[Any]) → Labels[source]#

Overrid to convert predictions to (class_id, scores) pairs.

Parameters

windows (Iterable[Box]) –
predictions (Iterable[Any]) –

Return type

Labels

get_cell_class_id(cell: Box) → int[source]#

Return class_id for a cell.

Parameters: cell (Box) – (Box)
Return type: int

get_cell_scores(cell: Box) → Optional[Sequence[float]][source]#

Return scores for a cell.

Parameters: cell (Box) – (Box)
Return type: Optional[Sequence[float]]

get_cells() → List[Box][source]#

Return list of all cells (list of Box).

Return type: List[Box]

get_class_ids() → List[int][source]#

Return list of class_ids for all cells.

Return type: List[int]

get_scores() → List[Optional[Sequence[float]]][source]#

Return list of scores for all cells.

Return type: List[Optional[Sequence[float]]]

get_singleton_labels(cell: Box)[source]#

Return Labels object representing a single cell.

Parameters: cell (Box) – (Box)

get_values() → List[ClassificationLabel][source]#

Return list of class_ids and scores for all cells.

Return type: List[ClassificationLabel]

classmethod make_empty() → ChipClassificationLabels[source]#

Instantiate an empty instance of this class.

Returns: An object of the Label subclass on which this method is called.
Return type: Labels

save(uri: str, class_config: ClassConfig, crs_transformer: CRSTransformer) → None[source]#

Save labels as a GeoJSON file.

Parameters

uri (str) – URI of the output file.
class_config (ClassConfig) – ClassConfig to map class IDs to names.
crs_transformer (CRSTransformer) – CRSTransformer to convert from pixel-coords to map-coords before saving.

Return type

None

set_cell(cell: Box, class_id: int, scores: Optional[ndarray] = None) → None[source]#

Set cell and its class_id.

Parameters

cell (Box) – (Box)
class_id (int) – int
scores (Optional[ndarray]) – 1d numpy array of probabilities for each class

Return type

None