Semantic inference rfcr

operators.ml3d.semantic_inference_rfcr(client, data_in_path='data.laz', results_labels_path='result_labels.labels', results_probabilities_path='result_probabilities.npy', in_model_parameters_path='results/Log_2022-11-10_11-42-05', number_of_votes=5, feature_names='red,green,blue', point_names='x,y,z', instance_type='x2large')

semantic_inference_rfcr( client,

data_in_path=’data.laz’,

results_labels_path=’result_labels.labels’,

results_probabilities_path=’result_probabilities.npy’,

in_model_parameters_path=’results/Log_2022-11-10_11-42-05’,

number_of_votes=5,

feature_names=’red,green,blue’,

point_names=’x,y,z’,

instance_type=’x2large’ )

Parameters:

• data_in_path – path to data

• results_labels_path – path to labels

• results_probabilities_path – path to probabilities

• in_model_parameters_path – path to model

• number_of_votes – number of votes to vote for a class

• feature_names – comma separated list of features that are provided

• point_names – comma separated list of point identifiers in (las/laz)

• instance_type – type of cloud instance used for processing