TengineKit - Free, Fast, Easy, Real-Time Face Detection & Face Landmarks & Face Attributes & Hand Detection & Hand Landmarks & Body Detection & Body Landmarks & Iris Landmarks & Yolov5 SDK On Mobile.
This is an official implementation of facial landmark detection for our TPAMI paper "Deep High-Resolution Representation Learning for Visual Recognition". https://arxiv.org/abs/1908.07919
PyTorch implementation of "Super-Realtime Facial Landmark Detection and Shape Fitting by Deep Regression of Shape Model Parameters" predicting facial landmarks with up to 400 FPS
This HCI (Human-Computer Interaction) application in Python(3.6) will allow you to control your mouse cursor with your facial movements, works with just your regular webcam. Its hands-free, no wearable hardware or sensors needed.
This deep learning application can detect Facial Keypoints (15 unique points). They mark important areas of the face - the eyes, corners of the mouth, the nose, etc.
The facial detection API allows us to not only detect faces & facial features but also check those faces for particular properties such as if a smile is present or eyes are open etc. This is a simple app that recognizes a face in a photo and highlights it with a box. Also, it captures facial features like eyes, nose, lips, ears etc. All written i Swift4.
The python code detects different landmarks on the face and predicts the emotions such as smile based on it. It automatically takes a photo of that person when he smiles. Also when the two eyebrows are lifted up, the system plays a music automatically and the music stops when you blink your right eye.
A good feature to automate the benchmarking is to add a module for automatic dataset download.