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A Lightweight Face Recognition and Facial Attribute Analysis (Age, Gender, Emotion and Race) Library for Python
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!
The Face Recognition SDK with face liveness, face matching and face compare by employing face anti-spoofing, face landmarking and face feature extraction
FaceRecognition. Machine Learning project to recognise people from an Image just like facebook. Built with the help of 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. Dependencies: Python 3.x. Numpy. Scipy. Scikit-learn. dlib.
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/.
Jun 18, 2018 · Learn how to perform face recognition using OpenCV, Python, and dlib by applying deep learning for highly accurate facial recognition.
3. Real time face detection. As previously, the algorithm is pretty easy to implement. We are also implementing a lighter version by detecting only the face. Dlib makes it really easy to detect facial keypoints too, but it’s another topic.
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.
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.
Apr 28, 2021 · 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.
