A face recognition API
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Updated
Feb 20, 2022 - Python
A face recognition API
Facial Liveness Detection on webcam, trained on combined multiple datasets
Easy and simple face recognition with high FPS, antispoof, and face detection
Simple Django health check
AI-Proctoring Framework runs in the background on the examinee’s machine, and tracks any kind of unwanted (Suspicious) activity of the candidate. Mouth Tracking, Blink Detection, Gaze Detection, Object Detection & Liveness Detection are few of the algorithms implemented in this Framework.
Realtime Face Anti Spoofing with Face Detector based on Deep Learning using Tensorflow/Keras and OpenCV
eKYC (Electronic Know Your Customer) is a project designed to electronically verify the identity of customers
This is the Face Liveness Detection Python project for Windows.
Zalo AI Challenge 2022 Liveness Detection
A strong baseline for liveness detection. The source code could be used for similar tasks, such as face anti-spoofing or detecting fake videos
Liveness Tests For Facial Recognition
libfaceid is a research framework for fast prototyping of face recognition solutions. It seamlessly integrates multiple face detection, face recognition and liveness detection models. It also includes face landmark detection, age detection, gender detection, emotion detection, wakeword/triggerword/hotword detection and text-to-speech synthesis f…
Face detection and recognition + liveness detection and spoofing attack recognition using onnxruntime. Includes an easy-to-use Flask API and Dockerfile.
Code and pre-trained models for detecting spoofing attacks from images.
This repository is a docker project for 3D passive face liveness detection (face anti-spoofing).
Face Recognition Web application Login with liveness detection for Anti-Spoofing
lock mechanism with face recognition and liveness detection
face liveness detection activate, the script asks the person to generate an action, for example one of the actions they may ask you to do is smile, turn your face to the right, get angry, blink, etc. The actions are requested randomly, after fulfilling all the actions it generates a message saying "liveness successful" or "liveness fail"
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