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)
elif task == '8':
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)
binary_image_metadata_matrix = metadata.get_binary_image_metadata()
k = int(input("Enter the number of latent features to consider: "))
nmf = NMFModel(binary_image_metadata_matrix, k, images_list)
nmf.decompose()
print('Decomposition Complete')
nmf.print_term_weight_pairs(k)
else:
print('Please enter the correct task number !')
