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|MIT License||MIT License|
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Query regarding Multiple face recognization system
2 projects | reddit.com/r/MLQuestions | 25 Nov 2021
It's generally better to split the task into a multiple tasks. First I'd want to detect and extract faces. There are a number of pretrained models that you could use for that, e.g. https://github.com/timesler/facenet-pytorch, https://github.com/opencv/opencv/tree/master/data/haarcascades. Once you've extracted faces, you can train a facial recognition using something like a siamese network as you normally would.
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Tracking mentions began in Dec 2020.
What are some alternatives?
anime-face-detector - Anime Face Detector using mmdet and mmpose
CompreFace - Leading free and open-source face recognition system
pytorch2keras - PyTorch to Keras model convertor
OpenCV - Open Source Computer Vision Library
DeepCamera - Empower any camera/CCTV with state of the art AI, including facial recognition, person recognition(RE-ID) car detection, fall detection and more
DeepFake-Detection - Towards deepfake detection that actually works
OpenSeeFace - Robust realtime face and facial landmark tracking on CPU with Unity integration
facenet - Face recognition using Tensorflow
Real-time-GesRec - Real-time Hand Gesture Recognition with PyTorch on EgoGesture, NvGesture, Jester, Kinetics and UCF101
Face Recognition - The world's simplest facial recognition api for Python and the command line
face-alignment - :fire: 2D and 3D Face alignment library build using pytorch
pytorch_resnet_cifar10 - Proper implementation of ResNet-s for CIFAR10/100 in pytorch that matches description of the original paper.