Open Source Facial Recognition Software
Sort By:
Facial Recognition Software
View 117 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.
-
Gemini 3 and 200+ AI Models on One PlatformBuild generative AI apps with Vertex AI. Switch between models without switching platforms.
-
Try Google Cloud Risk-Free With $300 in CreditUse your credit across every product. Compute, storage, AI, analytics. When it runs out, 20+ products stay free. You only pay when you choose to.
-
1
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. -
2
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. -
3
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. -
4
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. -
AI-generated apps that pass security reviewRetool lets you generate dashboards, admin panels, and workflows directly on your data. Type something like “Build me a revenue dashboard on my Stripe data” and get a working app with security, permissions, and compliance built in from day one. Whether on our cloud or self-hosted, create the internal software your team needs without compromising enterprise standards or control.
-
5
FaceRecognitionDotNet
The world's simplest facial recognition api for .NET on Windows, MacOS
The world's simplest facial recognition API for .NET on Windows, MacOS, and Linux. -
6
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. -
7
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 -
8
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. -
9
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 -
Easily Host LLMs and Web Apps on Cloud RunRun frontend and backend services, batch jobs, host LLMs, and queue processing workloads without the need to manage infrastructure. Cloud Run gives you on-demand GPU access for hosting LLMs and running real-time AI—with 5-second cold starts and automatic scale-to-zero so you only pay for actual usage. New customers get $300 in free credit to start.
-
10
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/ -
11
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. -
12
StReAV is a software which runs on Linux, loaded onto a PDA/handheld, into which the an audio and video capturing tool which could be easily clamped onto the collar of a shirt is connected. Capture or stream your video, even use it for face recognition.
-
13
Delphi Face Detection
Delphi face detection
Delphi Face Detection Live Web Camera Delphi Face Recognition: https://sourceforge.net/projects/delphi-face-recognition/ For Live: Face Attendance System, Facial Emotion, Gender Recognition Security Application. Ethnicity/Nationality Recognition(Maybe Soon) Age? Works on IP Camera using RTSP. Runs on Windows XP to Windows 10 Available on MsAcceSS or SQLite Dataface! Depending on Request! You can reprogram / setup / configure / scale the Face Recognition accuracy! C++Builder Face Detection: FREE Source code! https://sourceforge.net/projects/cbuilder-opencv-face-detection/ C++Builder Face Recognition: https://sourceforge.net/projects/c-builder-face-recognition/ Technical Support is always online, thank you -
14
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.
-
15
Vision2u
free image processing software
Vision2u offers a free image processing software for personal use and research. Primary tasks of the image processing can be realized during simple operation of the software. Every Web cam owner can have simplest measuring, counting or tasks of monitoring done without high capital outlays. -
16
ADAPTEL
Face Recognition - Surveillance Software
Face Recognition - Surveillance Software -
17
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 -
18
-
19
This is project should implement different biometrics algorithms for fingerprint and face recognition.
-
20
Bush Face Recognition
Face recognition using OpenCV
-
21
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 -
22
C++Builder with OpenCv345 face detect
C++Builder face detection
Embarcadero C++ Builder Face Detection FREE Source Code! Delphi and C++Builder FACE RECOGNITION,.... here: C++Builder: https://sourceforge.net/projects/c-builder-face-recognition/ Delphi: https://sourceforge.net/projects/delphi-face-recognition/ -
23
CS203L-droneProject
Lab Project for CS203 @ DWC
Self contained sensor suit that can be attached to an autonomous platform and be used to search for and locate people, first via heat then by facial recognition. -
24
-
25
Computer Vision
Best Practices, code samples, and documentation for Computer Vision
In recent years, we've see an extra-ordinary growth in Computer Vision, with applications in face recognition, image understanding, search, drones, mapping, semi-autonomous and autonomous vehicles. A key part to many of these applications are visual recognition tasks such as image classification, object detection and image similarity. This repository provides examples and best practice guidelines for building computer vision systems. The goal of this repository is to build a comprehensive set of tools and examples that leverage recent advances in Computer Vision algorithms, neural architectures, and operationalizing such systems. Rather than creating implementations from scratch, we draw from existing state-of-the-art libraries and build additional utility around loading image data, optimizing and evaluating models, and scaling up to the cloud.
