Point cloud classification inference folder

operators.tdp.point_cloud_classification_inference_folder(client, folder_in='/folder_in', folder_out='/folder_out', model_path='network_parameters', cols_data='X,Y,Z', cols_labels='classification', worker_instance_type='P2', manager_instance_type='small', extension_file_in='.laz', extension_file_out='.labels', skip_existing_files=False)

point_cloud_classification_inference_folder(client,

folder_in=’/folder_in’,

folder_out=’/folder_out’,

model_path=’network_parameters’,

cols_data=’X,Y,Z’,

cols_labels=’classification’,

worker_instance_type=’P2’,

manager_instance_type=”small”,

extension_folder_in=”.laz”,

extension_folder_out=”.labels”,

skip_existing_files = False )

Parameters:

• model_path – path to model

• cols_data – attributes used

• cols_labels – label name

• folder_in – input folder

• folder_out – results folder

• worker_instance_type – cloud instance type of worker nodes

• manager_instance_type – cloud instance type of manager node

• extension_folder_in – File extension of files in folder for folder_in

• extension_folder_out – File extension of files in folder for folder_out

• skip_existing_files – skip files that already exist in the output folder