pointtree.visualization

Tools for visualizing processing results.

pointtree.visualization.color_instance_segmentation( point_cloud: DataFrame, instance_id_column: str, target_instance_id_column: str | None = None, fp_ids: List[int] | None = None, fn_ids: List[int] | None = None, ) → DataFrame[source]

Sets the color of each point based on its instance ID.

Parameters:

point_cloud (DataFrame) – Point cloud to be colored.
instance_id_column (str) – Name of the column containing the instance IDs.
target_instance_id_column (str | None) – Name of the column containing the ground truth instance IDs. (default: None)
fp_ids (List[int] | None) – List of the predicted tree IDs that represent false positives. If set to None, false positives are not colored by a dedicated color. (default: None)
fn_ids (List[int] | None) – List of the ground truth tree IDs that represents false negatives. If set to None, false negatives are not colored by a dedicated color. (default: None)

Returns:

Point cloud with added or modified “r”, “g”, “b”, “a” attributes.

Return type:

pandas.DataFrame

pointtree.visualization.color_semantic_segmentation( point_cloud: DataFrame, classes_to_colors: Dict[int, str], semantic_segmentation_column: str = 'classification', ) → DataFrame[source]

Sets the color of each point based on its semantic class.

Parameters:

point_cloud (DataFrame) – Point cloud to be colored.
classes_to_colors (Dict[int, str]) – Mapping of class IDs to hex color codes.
semantic_segmentation_column (str) – Name of the column containing semantic class IDs. Defaults to "classification". (default: 'classification')

Returns:

Point cloud with added or modified “r”, “g”, “b”, “a” attributes.

pointtree.visualization.hex_to_rgb(hex_color: str) → Tuple[float, float, float][source]

Converts hexadecimal color code to RGB color value.

Parameters:: hex – Hexadecimal color code.
Returns:: RGBA color value.

Plots a shape fitted to a set of 2D points. The shape to be plotted can either be a circle, an ellipse, or a polygon.

Parameters:

xy (ndarray[Any, dtype[float32 | float64]]) – Coordinates of the points to which the shape was fitted.
file_path (str | Path) – File path under which the image is to be saved.
circle (ndarray[Any, dtype[float32 | float64]] | None) – Parameters of the circle in the following order: x-coordinate of the center, y-coordinate of the center, radius. If set to None, no circle is plotted. (default: None)
ellipse (ndarray[Any, dtype[float32 | float64]] | None) – Parameters of the ellipse in the following order: x- and y-coordinates of the center, radius along the semi-major, radius along the semi-minor axis, and the counterclockwise angle of rotation from the x-axis to the semi-major axis of the ellipse. If set to None, no ellipse is plotted. (default: None)
polygon (ndarray[Any, dtype[float32 | float64]] | None) – Sorted vertices (x- and y-coordinates) of the polygon. If set to None, no polygon is plotted. (default: None)

Shape:

xy: \((N, 2)\)
circle: \((3)\)
ellipse: \((5)\)
polygon: \((V)\)

where

\(N = \text{ number of points}\)
\(V = \text{ number of polygon vertices}\)

pointtree.visualization.save_tree_map( image: ndarray, output_path: str, *, is_label_image: bool = False, crown_borders: ndarray[Any, dtype[bool_]] | None = None, border_mask: ndarray[Any, dtype[bool_]] | None = None, seed_mask: ndarray[Any, dtype[bool_]] | None = None, core_mask: ndarray[Any, dtype[bool_]] | None = None, tree_positions: ndarray[Any, dtype[int64]] | None = None, crown_positions: ndarray[Any, dtype[int64]] | None = None, trunk_positions: ndarray[Any, dtype[int64]] | None = None, ) → None[source]: Saves a 2D map showing canopy height models, tree positions etc. as image file.