ownphotos - Self hosted Google Photos clone

  •        14

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.




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A library for performing face detection on windows phone 7. This library uses the same algorithms and detection models as OpenCV and is written in C# and built for the Windows Phone. Also includes a camera user control that supports automated taking of photos and showing camer...


  •    Javascript

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.

libface - Face Recognition Library

  •    C++

Libface is a cross platform framework for developing face recognition algorithms and testing its performance. The library uses OpenCV 2.0 and aims to be a middleware for developers that don’t have to include any OpenCV code in order to use face recognition and face detection detection.


  •    C++

SeetaFace Engine is an open source C++ face recognition engine, which can run on CPU with no third-party dependence. It contains three key parts, i.e., SeetaFace Detection, SeetaFace Alignment and SeetaFace Identification, which are necessary and sufficient for building a real-world face recognition applicaiton system. SeetaFace Detection implements a funnel-structured (FuSt) cascade schema for real-time multi-view face detection, which achieves a good trade-off between detection accuracy and speed. State of the art accuracy can be achieved on the public dataset FDDB in high speed. See SeetaFace Detection for more details.

pico - A minimalistic framework for fast object detection (with a pre-trained face detector)

  •    C

Those of you who would like to quickly see what this repository is all about, go to the folder rnt/sample. There you will find a sample program which will detect faces in a video stream supplied from the default webcam attached to the computer. Also, you can check out a demo video at http://www.youtube.com/watch?v=1lXfm-PZz0Q. In general, detection can be described as a task of finding the positions and scales of all objects in an image that belong to a given appearance class. For example, these objects could be cars, pedestrians or human faces. Automatic object detection has a broad range of applications. Some include biometrics, driver assistance, visual surveillance and smart human-machine interfaces. These applications create a strong motivation for the development of fast and accurate object detection methods.

sod - An Embedded Computer Vision & Machine Learning Library (CPU Optimized & IoT Capable)

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SOD is an embedded, modern cross-platform computer vision and machine learning software library that expose a set of APIs for deep-learning, advanced media analysis & processing including real-time, multi-class object detection and model training on embedded systems with limited computational resource and IoT devices. SOD was built to provide a common infrastructure for computer vision applications and to accelerate the use of machine perception in open source as well commercial products.

DeepVideoAnalytics - A distributed visual search and visual data analytics platform.

  •    Python

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.

openface - Face recognition with deep neural networks.

  •    Lua

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.

VisionFaceDetection - An example of use a Vision framework for face landmarks detection in iOS 11

  •    Swift

First one is face rectangle detection by using VNDetectFaceRectanglesRequest based on pixelBuffer provided by delegate function captureOutput. Next we need to setup the property inputFaceObservations of VNDetectFaceLandmarksRequest object, to provide the input. Now we are redy to start landmarks detection.

facenet - Face recognition using Tensorflow

  •    Python

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.

faint - The Face Annotation Interface

  •    Java

Java framework for face detection and face recognition based on different plugin and filter types. Includes Eigenfaces in pure Java, OpenCV detection via JNI, integration of the Betaface.com Web Service, skin color filter, Adobe XMP Export and a nice GUI

Face-It - A repository of Processing examples for ITP fall workshop about face detection, recognition, and miscellaneous tracking methods

  •    Processing

A "syllabus" and repository of Processing examples for ITP fall workshop about face detection, recognition, and miscellaneous tracking methods.

jeelizFaceFilter - Javascript/WebGL lightweight face tracking library designed for augmented reality webcam filters

  •    Javascript

This JavaScript library detects and tracks the face in real time from the webcam video feed captured with WebRTC. Then it is possible to overlay 3D content for augmented reality applications. We provide various demonstrations using main WebGL 3D engines. We have included in this repository the release versions of the 3D engines to work with a determined version (they are in /libs/<name of the engine>/). This library is lightweight and it does not include any 3D engine or third party library. We want to keep it framework agnostic so the outputs of the library are raw: if the a face is detected or not, the position and the scale of the detected face and the rotation Euler angles. But thanks to the featured helpers, examples and boilerplates, you can quickly deal with a higher level context (for motion head tracking, for face filter or face replacement...). We continuously add new demontrations, so stay tuned ! Also, feel free to open an issue if you have any question or suggestion.

face_recognition - The world's simplest facial recognition api for Python and the command line

  •    Python

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.

sphereface - Implementation for <SphereFace: Deep Hypersphere Embedding for Face Recognition> in CVPR'17

  •    Jupyter

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.

jeelizWeboji - JavaScript/WebGL real-time face tracking and expression detection library

  •    Javascript

With this library, you can build your own animoji embedded in Javascript/WebGL applications. You do not need any specific device except a standard webcam. By default a webcam feedback image is displayed with the face detection frame. The face detection is quite robust to all lighting conditions, but the evaluation of expression can be noisy if the lighting is too directional, too weak or if there is an important backlight. So the webcam feedback image is useful to see the quality of the input video feed.

android-face-detector - A real-time face detection Android library

  •    Kotlin

Face detector is a face detection Android library which can be easily plugged into any camera API (given it provides a way to process its frames). Face detector is built on top of Firebase ML Kit's face detection API.

OpenBR - Open Source Biometric Recognition

  •    C++

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.

digiKam - Advanced Digital Photo Management

  •    C++

digiKam is an advanced digital photo management application for KDE, which makes importing and organizing digital photos a snap. The photos can be organized in albums which can be sorted chronologically, by directory layout or by custom collections. It provides support to add tag, comment to your images.