Open Source Facial Recognition Software
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Facial Recognition Software
View 108 business solutionsBrowse free open source Facial Recognition software and projects below. Use the toggles on the left to filter open source Facial Recognition software by OS, license, language, programming language, and project status.
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InsightFace
State-of-the-art 2D and 3D Face Analysis Project
State-of-the-art deep face analysis library. InsightFace is an open-source 2D&3D deep face analysis library. InsightFace is an integrated Python library for 2D&3D face analysis. InsightFace efficiently implements a wide variety of state-of-the-art algorithms for face recognition, face detection, and face alignment, which are optimized for both training and deployment. Research institutes and industrial organizations can get benefits from InsightFace library. -
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Face Recognition
World's simplest facial recognition api for Python & the command line
Face Recognition is the world's simplest face recognition library. It allows you to recognize and manipulate faces from Python or from the command line using dlib's (a C++ toolkit containing machine learning algorithms and tools) state-of-the-art face recognition built with deep learning. Face Recognition is highly accurate and is able to do a number of things. It can find faces in pictures, manipulate facial features in pictures, identify faces in pictures, and do face recognition on a folder of images from the command line. It could even do real-time face recognition and blur faces on videos when used with other Python libraries. -
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OpenFace Face Recognition
Face recognition with deep neural networks
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. 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. Accuracies from research papers have just begun to surpass human accuracies on some benchmarks. The accuracies of open source face recognition systems lag behind the state-of-the-art. See our accuracy comparisons on the famous LFW benchmark. -
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VGGFace2
VGGFace2 Dataset for Face Recognition
VGGFace2 is a large-scale face recognition dataset developed to support research on facial recognition across variations in pose, age, illumination, and identity. It consists of 3.31 million images covering 9,131 subjects, with an average of over 360 images per subject. The dataset was collected from Google Image Search, ensuring a wide diversity in ethnicity, profession, and real-world conditions. It is split into a training set with 8,631 identities and a test set with 500 identities, making it suitable for benchmarking and large-scale model training. Alongside the dataset, the repository provides pre-trained models based on ResNet-50 and SE-ResNet-50 architectures, trained with both MS-Celeb-1M pretraining and fine-tuning on VGGFace2. These models achieve strong verification performance on benchmarks such as IJB-B and include variants with lower-dimensional embeddings for compact feature representation. The project also includes preprocessing tools, face detection scripts, and etc. -
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EMGU Face Recognition
Using EMGU to perform Principle Component Analysis (PCA)
This article is designed to be the first in several to explain the use of the EMGU image processing wrapper. For more information on the EMGU wrapper please visit the EMGU website. You will start with 3 warnings for the references not being found. Expand the References folder within the solution explorer delete the 3 with yellow warning icons and Add fresh references to them. Face Recognition has always been a popular subject for image processing and this article builds upon the good work by Sergio Andrés Gutiérrez Rojas and his original article (codeproject). The reason that face recognition is so popular is not only it’s real world application but also the common use of principle component analysis (PCA). PCA is an ideal method for recognising statistical patterns in data. The popularity of face recognition is the fact a user can apply a method easily and see if it is working without needing to know to much about how the process is working. -
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PRISH OS is custom os based on latest J6 Q update with ONEUI 2 for Exynos 7870 Powered devices ported and maintained by NEEL0210 and team.
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Delphi Face Recognition March_01_2019
Delphi Face Recognition
Donate $108 for FULL source code of the project. Donate and message or mail at dbinxecod@gmail.com RTSP url link updated BUG FIXED! MEMORY LEAK! ADDED 64BIT + TBB HARD BOILED FACE RECOGNITION: https://sourceforge.net/projects/delphi-face-recognizer/ Gate ID Multi Face Recognition: $384 https://sourceforge.net/projects/opencv-multi-face-detect/ Delphi Face Detection: FREE Source code! https://sourceforge.net/projects/delphi-opencv-face-detection/ Works on IP Camera using RTSP. Runs on Windows XP to Windows 10 using SQLite Dataface! You can reprogram / setup / configure / scale the Face Recognition accuracy! C++Builder Face Recognition: FREE source code of single FR. https://sourceforge.net/projects/c-builder-face-recognition/ C++Builder Face Detection: FREE Source code https://sourceforge.net/projects/cbuilder-opencv-face-detection/ Technical Support is always online -
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Exadel CompreFace
Leading free and open-source face recognition system
Exadel CompreFace is a free and open-source face recognition GitHub project. Essentially, it is a docker-based application that can be used as a standalone server or deployed in the cloud. You don’t need prior machine learning skills to set up and use CompreFace. The system provides REST API for face recognition, face verification, face detection, face mask detection, landmark detection, age, and gender recognition. The solution also features a role management system that allows you to easily control who has access to your Face Recognition Services. CompreFace is delivered as a docker-compose config and supports different models that work on CPU and GPU. Our solution is based on state-of-the-art methods and libraries like FaceNet and InsightFace. Official website: https://exadel.com/solutions/compreface/ Github link: https://github.com/exadel-inc/CompreFace -
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Its a Face Recognition File Manager i Developed in JAVA with a Native c++ to interface with a free Face Recognition SDK that i implemented which was written in C language. IT SUPPORTS LIVE UPDATES
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Store Management System
system which works as electronic notebook for keeping records...
Visit our site given below for the LATEST UPDATE and guide for use of store management system on https://tmotagam.github.io/ Shop management system which works as electronic notebook it keeps data about sales and also of products it has Point of sale backups and inventory system WHAT`S NEW: Added New Icon We have launched new project FTPT for sharing your files with your teams using ftp go check it out LINK https://sourceforge.net/projects/ftpt/ We have launched new project Tahafacex for attendance systems using face recognition technology. A great and easy to use interface, can be used in any environment from business to schools to colleges go check it out LINK https://sourceforge.net/projects/tahafacex/ -
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Meihu-FaceBeauty-Live
Beauty can be applied to live broadcasts, short videos, and selfies
Meihu beauty sdk is a mobile sdk with face recognition technology as the core, providing professional-grade real-time beauty, big eyes and face reduction, beauty filters, dynamic stickers and other filters, to create a multi-functional video beauty software The goal is to fully meet the beautification needs of customers in many audio and video software business scenarios such as live beauty and short video beauty. The open source version is now available for iOS, and the Android open source version is under development, so stay tuned! -
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This program broken The program is a real-time face detection application built using OpenCV and Tkinter. It allows you to detect faces using your webcam and displays the video feed with rectangles drawn around the detected faces. When you run the program, a GUI window will appear. The window has a title "Real-time Face Detection" and a description below it. The description guides you to adjust the settings and click the "Start" button to begin face detection. The settings section provides two adjustable parameters: Scale Factor: It is represented by a slider. You can modify the scale factor by moving the slider. The scale factor controls the size of the image pyramid used for face detection. Higher values increase the chance of detecting smaller faces. Min Neighbors: It is also represented by a slider. You can adjust the minimum number of neighboring rectangles required for a region to be considered as a face. Higher values increase reliability but may miss some faces.
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The Human Body Project allows computers to better understand and interact with people. Using a webcam the system can detect and recognise individuals (face recognition), identify their gaze direction, facial expressions and upper body postures.
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Face Recognition based attendance system which can also be used for security purposes In the Install directory, navigate to Vissemantics/Vissemantics Face Attendance/latestwinalphadistr/winalphadistr/dist/main and run main.exe Please change facial data password to desired password after entering application by clicking on Help and Change Password. Old Password is 'vissemantics'.
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Blazeface
Blazeface is a lightweight model that detects faces in images
Blazeface is a lightweight, high-performance face detection model designed for mobile and embedded devices, developed by TensorFlow. It is optimized for real-time face detection tasks and runs efficiently on mobile CPUs, ensuring minimal latency and power consumption. Blazeface is based on a fast architecture and uses deep learning techniques to detect faces with high accuracy, even in challenging conditions. It supports multiple face detection in varying lighting and poses, and is designed to work in real-world applications like mobile apps, robotics, and other resource-constrained environments. -
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Libface is a cross platform framework for developing face recognition algorithms and testing its performance.
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Face Recognition System
Face Recognition System Matlab source code
Research on automatic face recognition in images has rapidly developed into several inter-related lines, and this research has both lead to and been driven by a disparate and expanding set of commercial applications. The large number of research activities is evident in the growing number of scientific communications published on subjects related to face processing and recognition. Index Terms: face, recognition, eigenfaces, eigenvalues, eigenvectors, Karhunen-Loeve algorithm. -
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MediaPipe Face Detection
Detect faces in an image
The MediaPipe Face Detection model is a high-performance, real-time face detection solution that uses machine learning to identify faces in images and video streams. It is optimized for mobile and embedded platforms, offering fast and accurate face detection while maintaining a small memory footprint. This model supports multiple face detections and is highly efficient, making it suitable for a variety of applications such as augmented reality, user authentication, and facial expression analysis. -
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The development of a biometric system and applications e.g. Access Control based on the system to recognize and verify people. The primary goal is face recognition, but other human attributes might get used too in the future.
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ADAPTEL
Face Recognition - Surveillance Software
Face Recognition - Surveillance Software -
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Accord.Net Face Detection Recognition
Accord.Net Face Detection Recognition
The most simplest clean hard core code for Accord.Net Face Detection with Face Cropping in Cs Vb for **** FACE RECOGNITION **** using Accord.Net like the first screenshot contact dbinxecod@gmail.com Full source code ahead for face recognition using Accort.Net Donate for $108 then you'll get the full source code! Please see screen shot of face recognition via Accord.NET -
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This is project should implement different biometrics algorithms for fingerprint and face recognition.
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Bush Face Recognition
Face recognition using OpenCV
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C++Builder Face Recognition March01_2019
C++Builder Face Recognition
RTSP url link updated Donote $108 for FULL source code of the project. BUG FIXED! MEMORY LEAK! ADDED 64_BIT + TBB HARD BOILED FACE RECOGNITION: https://sourceforge.net/projects/cbuilder-face-recognizer/ page not found for hard core c++Builder, contact author! https://sourceforge.net/projects/delphi-face-recognizer/ C++Builder Face Detection: FREE Source code! https://sourceforge.net/p/cbuilder-opencv-face-detection/ For Live: Face Attendance System, Facial Emotion, Gender Recognition Works on IP Camera using RTSP. ---> After you Donate, message or mail at dbinXecod@gmail.com ---> Runs on Windows XP to Windows 10 using SQLite Dataface! You can reprogram / setup / configure / scale the Face Recognition accuracy! Delphi Face Detection: FREE Source code! https://sourceforge.net/projects/delphi-opencv-face-detection/ Delphi Face Recognition: https://sourceforge.net/projects/delphi-face-recognition/ Technical Support is always online