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A Lightweight Face Recognition and Facial Attribute Analysis (Age, Gender, Emotion and Race) Library for Python
The Face Recognition SDK with face liveness, face matching and face compare by employing face anti-spoofing, face landmarking and face feature extraction
kby-ai / FaceRecognition-Flutter. Face recognition Flutter with 3D passive liveness detection (anti-spoofing). This repo supports the following functionality: face matching, face compare, face comparison, facial recognition, feature extraction, face anti-spoofing and face liveness for IDV.
The world's simplest facial recognition api for Python and the command line. python machine-learning face-recognition face-detection. Updated last month. Python. deepinsight / insightface. Star 22.1k. Code. Issues. Pull requests. State-of-the-art 2D and 3D Face Analysis Project.
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Built using dlib's state-of-the-art face recognition built with deep learning. The model has an accuracy of 99.38% on the Labeled Faces in the Wild benchmark. This also provides a simple face_recognition command line tool that lets you do face recognition on a folder of images from the command line!
In this repository, we implement and review state of the art papers in the field of face recognition and face detection, and perform operations such as face verification and face identification with Deep models like Arcface, MTCNN, Facenet and so on.
Aug 1, 2002 · A real time face recognition system developed in Python using Pillow, OpenCV and NumPy The steps to run this project are as follows: Create two empty folders named 'dataset' and 'trainer' in your main folder after unzipping.
OpenFace is a Python and Torch implementation of face recognition with deep neural networks and is based on the CVPR 2015 paper FaceNet: A Unified Embedding for Face Recognition and Clustering by Florian Schroff, Dmitry Kalenichenko, and James Philbin at Google. Torch allows the network to be executed on a CPU or with CUDA.
This project utilizes OpenCV Library to make a Real-Time Face Detection using your webcam as a primary camera. Approach/Algorithms used: 1.This project uses LBPH (Local Binary Patterns Histograms) Algorithm to detect faces.
