k = int(input("Please specify the number of components : ")) decomposition = Decomposition(decomposition_model, k, model, test_dataset_path, metadata_images_list=metadata_images_list, metadata_label=metadata_label) decomposition.dimensionality_reduction() test_image_id = input("Please specify test image ID: ") pickle_file_path = model + "_" + decomposition_model + "_" + metadata_label labels_list = ['Left_Right', 'Dorsal_Palmar', 'Gender', 'Accessories'] metadata_given = Metadata(metadata_images_list) metadata_given.set_unlabeled_image_features(model, test_image_id, decomposition) metadata_given.set_metadata_image_features(pickle_file_path) unlabeled_list = [] for label in labels_list: unlabeled_list.append(metadata_given.get_binary_label(label)) print('Labels of the unlabeled image are: ') print(unlabeled_list) elif task == '6': test_dataset_folder_path = os.path.abspath( os.path.join(Path(os.getcwd()).parent, test_dataset_path)) images_list = list( misc.get_images_in_directory(test_dataset_folder_path).keys()) metadata = Metadata(images_list)