Point cloud filter label noise folder

operators.tdp.point_cloud_filter_label_noise_folder(client, folder_in_data='/folder_in_data', folder_in_labels='/folder_in_labels', folder_out='/folder_out', k_nearest_neighbours=5, sigma=10.0, dim=3, invalid_label=0, worker_instance_type='P2', manager_instance_type='small', extension_file_in_data='.laz', extension_file_in_labels='.labels', extension_file_out='.laz', skip_existing_files=False)

point_cloud_filter_label_noise_folder(client,

folder_in_data=’/folder_in_data’,

folder_in_labels=’/folder_in_labels’,

folder_out=’/folder_out’,

k_nearest_neighbours=5,

sigma=10.,

dim=3,

invalid_label=0,

worker_instance_type=’P2’,

manager_instance_type=”small”,

extension_folder_in_data=”.laz”,

extension_folder_in_labels=”.labels”,

extension_folder_out=”.laz”,

skip_existing_files = False )

Parameters:

• k_nearest_neighbours – k nearest neighbours

• sigma – sigma

• dim – dim

• invalid_label – invalid class label

• folder_in_data – input folder data

• folder_in_labels – input folder labels

• folder_out – output folder

• worker_instance_type – cloud instance type of worker nodes

• manager_instance_type – cloud instance type of manager node

• extension_folder_in_data – File extension of files in folder for folder_in_data

• extension_folder_in_labels – File extension of files in folder for folder_in_labels

• extension_folder_out – File extension of files in folder for folder_out

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