Knn classification

operators.ml3d.knn_classification(client, in_path_to_points='new.laz', in_path_from_points='old.laz', out_path_labels='out.labels', out_path_probs='out.npy', k=3, max_distance=1.0, to_points_names='X,Y,Z', from_point_names='X,Y,Z', from_class_name='classification', instance_type='x2large')

knn_classification( client,

in_path_to_points=’new.laz’,

in_path_from_points=’old.laz’,

out_path_labels=’out.labels’,

out_path_probs=’out.npy’,

k=3,

max_distance=1.0,

to_points_names=’X,Y,Z’,

from_point_names=’X,Y,Z’,

from_class_name=’classification’,

instance_type=’x2large’ )

Parameters:

• in_path_to_points – input point cloud to be labeled

• in_path_from_points – input reference point cloud

• out_path_labels – out class labels

• out_path_probs – out class probabilities

• k – number of neighbors

• max_distance – maximum distance

• to_points_names – names of points to be labeled

• from_point_names – names of reference points

• from_class_name – name of reference classification

• instance_type – type of cloud instance used for processing