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facenet - Face recognition using Tensorflow
This is a TensorFlow implementation of the face recognizer described in the paper "FaceNet: A Unified Embedding for Face Recognition and Clustering". The project also uses ideas from the paper "Deep Face Recognition" from the Visual Geometry Group at Oxford. The code is tested using Tensorflow r1.7 under Ubuntu 14.04 with Python 2.7 and Python 3.5. The test cases can be found here and the results can be found here.
face-recognition tensorflow facenet deep-learning computer-vision face-detection mtcnn neural-networksopenface - Face recognition with deep neural networks.
Free and open source face recognition with deep neural networks. This research was supported by the National Science Foundation (NSF) under grant number CNS-1518865. Additional support was provided by the Intel Corporation, Google, Vodafone, NVIDIA, and the Conklin Kistler family fund. Any opinions, findings, conclusions or recommendations expressed in this material are those of the authors and should not be attributed to their employers or funding sources.
deep-learning face-recognition facenet face-detection neural-networksDeepVideoAnalytics - A distributed visual search and visual data analytics platform.
Deep Video Analytics is a platform for indexing and extracting information from videos and images. With latest version of docker installed correctly, you can run Deep Video Analytics in minutes locally (even without a GPU) using a single command. Deep Video Analytics implements a client-server architecture pattern, where clients can access state of the server via a REST API. For uploading, processing data, training models, performing queries, i.e. mutating the state clients can send DVAPQL (Deep Video Analytics Processing and Query Language) formatted as JSON. The query represents a directed acyclic graph of operations.
deep-learning nvidia-docker face-recognition face-detection image-retrieval visual-search video-analytics cbir deep-video-analyticssphereface - Implementation for <SphereFace: Deep Hypersphere Embedding for Face Recognition> in CVPR'17
SphereFace is released under the MIT License (refer to the LICENSE file for details). 2018.8.14: We recommand an interesting ECCV 2018 paper that comprehensively evaluates SphereFace (A-Softmax) on current widely used face datasets and their proposed noise-controlled IMDb-Face dataset. Interested users can try to train SphereFace on their IMDb-Face dataset. Take a look here.
face-recognition caffe sphereface cvpr-2017 face-detection angular-softmax deep-learningface_verification_experiment
The Deep Face Representation Experiment is based on Convolution Neural Network to learn a robust feature for face verification task. The popular deep learning framework caffe is used for training on face datasets such as CASIA-WebFace, VGG-Face and MS-Celeb-1M. And the feature extraction is realized by python code caffe_ftr.py. The single convolution net testing is evaluated on unsupervised setting only computing cosine similarity for lfw pairs.
face-recognition caffeface_recognition - The world's simplest facial recognition api for Python and the command line
Recognize and manipulate faces from Python or from the command line with the world's simplest face recognition library. 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.
machine-learning face-detection face-recognitionface-api
JavaScript API for face detection and face recognition in the browser with tensorflow.js
face-recognition face js tensorflow tfjs neural-network resnet-34 convolutional-neural-networks face-detection face-similarity ssd-mobilenet face-landmarks mtcnn yolov2 tiny-yolo detection recognition tfface-recognition
Simple Node.js API for robust face detection and face recognition. This a Node.js wrapper library for the face detection and face recognition tools implemented in dlib. Installing the package will build dlib for you and download the models. Note, this might take some time.
face-detection face-recognition face nodejs node face-landmark typescript detection recognitioninsightface - Face Recognition Project on MXNet
2018.03.14: train_softmax.py(and a new image_iter.py) is now more clear after removing experimental code. All experimental and unstable test will be put on train.py and data.py. 2018.02.16: We put the MegaFace noise list in this repo. Please refer to [https://github.com/deepinsight/insightface/blob/master/src/megaface] for detail.
face-recognition mxnet neural-networkopencv - OpenCV projects: Face Recognition, Machine Learning, Colormaps, Local Binary Patterns, Examples
This repository contains OpenCV code and documents. More (maybe) here: https://www.bytefish.de.
opencv face-recognition machine-learningOpenBR - Open Source Biometric Recognition
OpenBR is a framework for investigating new modalities, improving existing algorithms, interfacing with commercial systems, measuring recognition performance, and deploying automated biometric systems. Off-the-shelf algorithms are also available for specific modalities including Face Recognition, Age Estimation, and Gender Estimation.
biometrics face-recognition recognition analysis image-analysis detectionEagleEye - Stalk your Friends
This only works if their Facebook Profile is public. You have at least one image of the person you are looking for and a clue about their name. You enter this data into EagleEye and it tries to find Instagram, Youtube, Facebook, and Twitter Profiles of this person.
python3 machine-learning face-recognition social-media stalkingownphotos - Self hosted Google Photos clone
Currently the project is in very early stages, so run it only for the sake of checking it out. Ownphotos comes with separate backend and frontend servers. The backend serves the restful API, and the frontend serves, well, the frontend. The easiest way to do it is using Docker.
backend photos docker face-detection face-recognition gallery selfhosted django django-rest-framework object-detection google-photosFaceCropper - :scissors: Crop faces, inside of your image, with iOS 11 Vision api.
To run the example project, clone the repo, and run pod install from the Example directory first. FaceCropper is available under the MIT license. See the LICENSE file for more info.
vision vision-api ios11 ios face-detection face-recognition faceLargeMargin_Softmax_Loss - Implementation for <Large-Margin Softmax Loss for Convolutional Neural Networks> in ICML'16
We introduce a large-margin softmax (L-Softmax) loss for convolutional neural networks. L-Softmax loss can greatly improve the generalization ability of CNNs, so it is very suitable for general classification, feature embedding and biometrics (e.g. face) verification. We give the 2D feature visualization on MNIST to illustrate our L-Softmax loss. The paper is published in ICML 2016 and also available at arXiv.
l-softmax icml-2016 lsoftmax-loss caffe face-recognition image-recognition deep-learningLightCNN - A Light CNN for Deep Face Representation with Noisy Labels, TIFS 2018
A pytorch implementation of A Light CNN for Deep Face Representation with Noisy Labels from the paper by Xiang Wu, Ran He, Zhenan Sun and Tieniu Tan. The official and original Caffe code can be found here. Download face dataset such as CASIA-WebFace, VGG-Face and MS-Celeb-1M.
pytorch face-recognitionFacial-Similarity-with-Siamese-Networks-in-Pytorch - Implementing Siamese networks with a contrastive loss for similarity learning
The goal is to teach a siamese network to be able to distinguish pairs of images. This project uses pytorch. Any dataset can be used. Each class must be in its own folder. This is the same structure that PyTorch's own image folder dataset uses.
pytorch-tutorial deep-learning neural-network siamese-network pytorch face-recognitionAMSoftmax - A simple yet effective loss function for face verification.
The paper is available as a technical report at arXiv. In this work, we design a new loss function which merges the merits of both NormFace and SphereFace. It is much easier to understand and train, and outperforms the previous state-of-the-art loss function (SphereFace) by 2-5% on MegaFace.
deep-learning face-recognition loss-functions metric-learning softmaxphp-opencv - PHP extensions for OpenCV
PHP extensions for OpenCV
php7 opencv php-extension php-opencv phpopencv face-recognition face-detection computer-vision php-facedetectfacerecognition_guide - This is a guide to face recognition with Python, GNU Octave/MATLAB and OpenCV2 C++
This is my guide to face recognition with OpenCV2 C++ and GNU Octave/MATLAB. If you research on face recognition, you'll soon notice there's a gigantic number of publications, but source code is very sparse. So this guide is here to change that. Two algorithms are explained and implemented with GNU Octave/MATLAB and OpenCV2 C++ namely Eigenfaces and Fisherfaces. To build the Python version of this document simply run make python, to build the Octave version of this document run make octave.
face-recognition matlab octave
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