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)
subject_id = int(input("Please input the subject Id : "))
sub_sub_list = metadata.sub_sub_list(subject_id)
if sub_sub_list[0] == tuple([-1, -1]):
print('Subject not present in the given dataset')
else:
