apply_augmentation.py

import pandas as pd

# Generate an augmented dataset using a transform table
augmentation_table = pd.read_csv('augmentation_table.csv', index_col='label_class')

augmentation_table.drop('label_name', axis=1, inplace=True)
augmentation_table.dropna(axis=0, how='all', inplace=True)

# Collect all global functions in global namespace
namespace = __import__(__name__)

def apply_augmentation(X, how=None):
    """Apply an augmentation function specified in `how` (string) to a numpy array X.
    
    Args:
        X: numpy array with images.
        how: a string with a function name to be applied to X, should return 
            the same-shaped numpy array as in X.
    
    Returns:
        Augmented X dataset.
    """
    assert augmentation_table.get(how) is not None
    
    augmentator = getattr(namespace, how)
    return augmentator(X)