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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
The world's simplest facial recognition api for Python and the command line. python machine-learning face-recognition face-detection. Updated 2 weeks ago. Python. deepinsight / insightface. Star 21.9k. Code. Issues. Pull requests. State-of-the-art 2D and 3D Face Analysis Project.
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...
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.
The program works as follow: Detect face (s) in the input image and crop out the face (s) only. Input the cropped face (s) into the embeddings generator, get the output embedding vector....
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.
State-of-the-art face recognition models are trained on millions of real human face images collected from the internet. DigiFace-1M aims to tackle three major problems associated with such large-scale face recognition datasets.
Jun 18, 2018 · Learn how to perform face recognition using OpenCV, Python, and dlib by applying deep learning for highly accurate facial recognition.
