An open source library for face detection in images. The face detection speed can reach 1000FPS.

Nodejs bindings to OpenCV 3 and OpenCV 4

TNN: developed by Tencent Youtu Lab and Guangying Lab, a uniform deep learning inference framework for mobile、desktop and server. TNN is distinguished by several outstanding features, including its cross-platform capability, high performance, model compression and code pruning. Based on ncnn and Rapidnet, TNN further strengthens the support and …

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.

face detection

Real-time image and video processing library similar to GPUImage, with built-in beauty filters, achieving commercial-grade beauty effects. Written in C++11 and based on OpenGL/ES.

[CVPR 2018] Real-Time Rotation-Invariant Face Detection with Progressive Calibration Networks

PHP extensions for OpenCV

Mediapipe-based library to redact faces from videos and images

Real time eye tracking for embedded and mobile devices.

Face tracking plugin for OBS Studio

small c++ library to quickly deploy models using onnxruntime

yoloface大礼包 使用pytroch实现的基于yolov3的轻量级人脸检测（包含关键点）

insightface-caffe

C++ project to implement MTCNN, a perfect face detect algorithm, on different DL frameworks. The most popular frameworks: caffe/mxnet/tensorflow, are all suppported now

face detection face recognition包含人脸检测(retinaface,yolov5face,yolov7face,yolov8face),人脸检测跟踪(ByteTracker)，人脸角度计算（Face_Angle）人脸矫正(Face_Aligner)，人脸识别(Arcface)，口罩检测(MaskRecognitiion)，年龄性别检测(Gender_age)，静默活体检测(Silent_Face_Anti_Spoofing),FaceAlignment(106keypoints)

使用OpenCV实现人脸关键点检测

3D Passive Face Liveness Detection (Anti-Spoofing) & Deepfake detection. A single image is needed to compute liveness score. 99,67% accuracy on our dataset and perfect scores on multiple public datasets (NUAA, CASIA FASD, MSU...).

A binary library for very fast face detection using compact CNNs.

This is an implematation project of face detection and recognition. The face detection using MTCNN algorithm, and recognition using LightenenCNN algorithm.