There are 1 repository under facenet-pytorch topic.
使用MTCNN进行人脸识别,FaceNet进行特征提取的人脸识别系统
eKYC (Electronic Know Your Customer) is a project designed to electronically verify the identity of customers
Real time face recognition Using Facenet , pytorch, Tensorflow
facenet-pytorch + DeepSORT
age estimation
Train FaceNet model with face masked augmentation on Pytorch.
Our Exploratory Project - On Person Identification
A robust pipeline for detecting and recognizing faces in video footage using YOLOv8 for detection and FaceNet-PyTorch for recognition, supporting real-time processing. Ideal for video surveillance and identity management.
A FaceRecognition module wrote with facenet_pytorch and Django as web framework
Final Year Project
Docker and Flask based API layer + data ingestion pipeline for the Facenet-PyTorch facial recognition library. I.e. simple ML deployment for matching pairs of photos
This project, developed with VS Code, Jupyter Notebook and Google Colab, uses Python (Flask, Pytorch, face_recognition, and more) and Postman (for API Testing) to develop two implementations of recognizing human faces, particularly those present in the LFW dataset and Indian Actors Dataset (both available on Kaggle).
Neural Networks, Dimensionality Reduction and Clustering
Analyzes of the Face Detection models
Detect The Face from the Input image and Recognize the person in Image from very few past examples.
Zillion Utility purpose Neural authentication Interface: ZUNI
university coursework - app for person identification
Live detection of person not wearing a mask
Reconocimiento facial con deep learning y python.
Service for identifying, determining the activity and involvement of the user in the process of distance learning
Face recognition and identity verification using deep learning
CZ4041 Machine Learning Project: Predicting probabilities of two images being kin
This project, developed with VS Code, Jupyter Notebook and Google Colab, uses Python (Flask, Pytorch, face_recognition, and more) and Postman (for API Testing) to develop two implementations of recognizing human faces, particularly those present in the LFW dataset and Indian Actors Dataset (both available on Kaggle).
Face Recognition System developed using PyTorch Face-Net and MTCNN modules. Detects and verifies user-selected faces.