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  1. A Lightweight Face Recognition and Facial Attribute Analysis (Age, Gender, Emotion and Race) Library for Python

  2. The Face Recognition SDK with face liveness, face matching and face compare by employing face anti-spoofing, face landmarking and face feature extraction

  3. 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!

  4. Differentiate between face recognition and face verification; Implement one-shot learning to solve a face recognition problem; Apply the triplet loss function to learn a network's parameters in...

  5. Real-time face recognition project with OpenCV and Python. Links for complete Tutorial: https://www.hackster.io/mjrobot/real-time-face-recognition-an-end-to-end-project-a10826 https://www.instructables.com/id/Real-time-Face-Recognition-an-End-to-end-Project/.

  6. Jan 19, 2016 · 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.

  7. Feb 7, 2018 · Face recognition identifies persons on face images or video frames. In a nutshell, a face recognition system extracts features from an input face image and compares them to the features of labeled faces in a database.

  8. justadudewhohacks.github.io › face-api › docsface-api.js - GitHub Pages

    To perform face recognition, one can use faceapi.FaceMatcher to compare reference face descriptors to query face descriptors. First, we initialize the FaceMatcher with the reference data, for example we can simply detect faces in a referenceImage and match the descriptors of the detected faces to faces of subsquent images:

  9. Face recognition is the most prominent biometric technique for identity authentication and is widely used in applications, such as access control, time attendance, finance, law enforcement, and public security.

  10. Best Open-Source Face Recognition Software. We studied github repositories of real-time open-source face recognition software and prepared a list of the best options: 1.Deepface. This library supports different face recognition methods like FaceNet and InsightFace.