def emotion_map(classes, N=1):
    """Take the most probable labels (output of postprocess) and return the 
    top N emotional labels that fit the picture."""
    emotion_table = {'neutral':0, 'happiness':1, 'surprise':2, 'sadness':3, 
                     'anger':4, 'disgust':5, 'fear':6, 'contempt':7}
    
    emotion_keys = list(emotion_table.keys())
    emotions = []
    for i in range(N):
        emotions.append(emotion_keys[classes[i]])
    return emotions