There are 4 repositories under face-mesh topic.
Human: AI-powered 3D Face Detection & Rotation Tracking, Face Description & Recognition, Body Pose Tracking, 3D Hand & Finger Tracking, Iris Analysis, Age & Gender & Emotion Prediction, Gaze Tracking, Gesture Recognition
MediaPipeのPythonパッケージのサンプルです。2024/9/1時点でPython実装のある15機能について用意しています。
使用ONNXRuntime部署3D人脸重建,人脸Mesh,人头姿势估计,包含C++和Python两个版本的程序
Open source 2D/3D face and body analysis library with toolkit for ML model retraining and generalization improvement.
Remote photoplethysmography (rPPG) is a contactless method to monitor human cardiac activities by detecting the pulse-induced subtle color variations on the human skin surface using a multi-wavelength RGB camera. By measuring the variance of red, green, and blue light reflection changes from the skin, as the contrast between specular reflection and diffused reflection.
Resources for understanding the output of MediaPipe's Face Mesh.
Open source 2D/3D face and body analysis library with toolkit for ML model retraining and generalization improvement.
In this project, I am creating a facial mesh using opencv and mediapipe. It can detect a face even with a face mask.
A python class consisting of all mediapipe funciton
This is a python module to include face-mesh
Convert your face to a Pixel Art!
Medical Face Mask Application Tool
A computer vision module based on opencv & mediapipe.
Face-Matrix approximate 3D facial surface geometry without the need for a depth sensor based on face-mesh in Tensorflow.js!
Real-time gesture recognition system using OpenCV and MediaPipe for detecting hand gestures, facial expressions, and body postures through computer vision.
Monitor viewing angle using Mediapipe Face mesh
Face Mesh Using Artificial Intelligence With the help of Media Pipe.
Face and iris detection using ONNX models in Python based on MediaPipe
Real-time face mesh detection project using OpenCV and MediaPipe in Python, providing detailed 3D facial landmark tracking and visualization capabilities.
Real-time face recognition system in Python that captures images, trains a model, and recognizes faces in a live video feed, displaying names near recognized faces.
This is a program that can be used to authenticate face using OpenCV
Starter Modules of Computer Vision ✨
This project involves developing a Face Mesh algorithm capable of mapping and identifying various facial features and contours.