A simple implementation of facial recognition using facenets for humans 🧔 🔍

This is a Human Attributes Detection program with facial features extraction. It detects facial coordinates using FaceNet model and uses MXNet facial attribute extraction model for extracting 40 types of facial attributes. This solution also detects Emotion, Age and Gender along with facial attributes.

<NOT ACTIVELY MAINTAINED>A light weight face recognition implementation using a pre-trained facenet model

Face recognition pipeline based on Facenet and MTCNN including image preprocessing (denoise, dehazing,...) with image augmentation techniques

Real time face recognition Using Facenet , pytorch, Tensorflow

A deep learning based application which is entitled to help the visually impaired people. The application automatically generates the textual description of what's happening in front of the camera and conveys it to person through audio. It is capable of recognising faces and tell user whether a known person is standing in front of him or not.

Face Recognition and Classification Using FaceNet and MTCNN

A Flask Rest API to register face to database and verification

This is a modern Face Authentication System which includes state-of-art algorithms to detect face and generate face embedding. This system contains endpoints which can be integrated to any device depending on the requirements.

Python application for face detection and recognition using various algorithms.

Attendance System using Open Face Model and Support Vector Machine

A Face Recognition using tensorflow. This code was copied from https://github.com/habrman/FaceRecognition/ and modified into an api to recognize faces of some celebrities

WYNA is a tiny bot asking your name and remembers your face and your name on next encounter

This project can detect a person and also recognize after trained on very limited data using Convolutional Nueral Network.

Detection and recognition of a person in real time live video sequences.

Automated registrations for meetups and events. Makes way for a constant and smooth flow for crowded events.

Smart attendance Desktop app built using facenet pr-trained model

This project uses Convolutional Neural Network to detect a person's face Using HAR feature. Then the person can be also recognized even if it was trained on only 1 image.