{'fraction_non_alphanumeric': 0.023255813953488372, 'fraction_numerical': 0.0, 'mean_word_length': 4.97029702970297, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Near real-time face parsing

Commercial applications like driver assistance programs in cars, smile detection softwares in cameras typically require reliable facial landmark points like the location of eyes, lips etc. and face pose at near real-time. Current methods are often unreliable, very cumbersome or computationally intensive. In this work, we focus on implementing a reliable and real-time method which parses an image and detects faces, estimates their pose and locates landmark points on the face. Our method builds on the existing literature. The method can work both for images and videos.