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:
print(sub_sub_list[0])
print(sub_sub_list[1])
print(sub_sub_list[2])
metadata.plot_subjects(subject_id, sub_sub_list, test_dataset_folder_path)
elif task == '7':
k = int(input("Enter the number of latent features to consider: "))
test_dataset_folder_path = os.path.abspath(
os.path.join(Path(os.getcwd()).parent, test_dataset_path))
decomposition = Decomposition(feature_extraction_model_name='SIFT',
test_folder_path=test_dataset_folder_path)
images_list = list(
misc.get_images_in_directory(test_dataset_folder_path).keys())
metadata = Metadata(images_list)
sub_sub_matrix = metadata.subject_matrix()
nmf = NMFModel(sub_sub_matrix, k, images_list)
nmf.decompose()
print('Decomposition Complete')
nmf.print_term_weight_pairs(k)
