Wireframe estimation inference folder

operators.ml3d.wireframe_estimation_inference_folder(client, in_folders='/in_folders', out_result_folders='/out_result_folders', in_model_path='parameters_wireframe', batch_size=1, worker_instance_type='x2large', manager_instance_type='small', extension_in_files='.laz', extension_out_result_files='.laz', skip_existing_files=False)

[hidden] Wireframe estimation inference: wireframe_estimation_inference_folder(client,

in_folders=’/in_folders’,

out_result_folders=’/out_result_folders’,

in_model_path=’parameters_wireframe’,

batch_size=1,

worker_instance_type=’x2large’,

manager_instance_type=”small”,

extension_in_folders=”.data_eval”,

extension_out_result_folders=”.result_wireframes”,

skip_existing_files = False )

Parameters:

in_model_path – model path
batch_size – batch size for training
in_folders – input folders or directory with training data
out_result_folders – output folders containing the wireframes
worker_instance_type – cloud instance type of worker nodes
manager_instance_type – cloud instance type of manager node
extension_in_folders – File extension of files in folder for in_folders
extension_out_result_folders – File extension of files in folder for out_result_folders
skip_existing_files – skip files that already exist in the output folder