Evaluate semantic segmentation folder

operators.ml3d.evaluate_semantic_segmentation_folder(client, prediction_folder='/prediction_folder', ground_truth_folder='/ground_truth_folder', class_names='1,2,3,4', invalid_label=0, worker_instance_type='x2large', manager_instance_type='small', extension_prediction_path='.labels', extension_ground_truth_path='.labels', skip_existing_files=False)

Evaluate semantic segmentation

evaluate_semantic_segmentation_folder(client,

prediction_folder=’/prediction_folder’,

ground_truth_folder=’/ground_truth_folder’,

class_names=’1,2,3,4’,

invalid_label=0,

worker_instance_type=’x2large’,

manager_instance_type=”small”,

extension_prediction_folder=”.labels”,

extension_ground_truth_folder=”.labels”,

skip_existing_files = False )

Parameters:

• class_names – class names

• invalid_label – Invalid label

• prediction_folder – Path to prediction folder or folder

• ground_truth_folder – Path to ground truth folder or folder

• worker_instance_type – cloud instance type of worker nodes

• manager_instance_type – cloud instance type of manager node

• extension_prediction_folder – File extension of files in folder for prediction_folder

• extension_ground_truth_folder – File extension of files in folder for ground_truth_folder

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