Projects sharing features with Real Time Face Recognition

OpenCV-Face-Recognition is a computer vision system designed to detect human faces and verify identities within live video streams and static images. It functions as a Python-based toolkit that processes visual data to locate facial boundaries and match detected features against a pre-trained database of profiles. The system utilizes a structured computer vision pipeline that integrates object detection with statistical analysis to perform identity verification. It employs pre-trained classifiers to scan for facial patterns and encodes facial textures into binary histograms to create represen

node-opencv is a high-performance C++ native addon and bridge that connects Node.js applications to the OpenCV library. It serves as an image processing toolkit and computer vision library, allowing JavaScript code to execute vision algorithms and image manipulation operations through native bindings. The project provides specialized capabilities for face and shape detection, as well as face identity recognition using trained models. It includes tools for object motion tracking through optical flow and background subtraction, along with the ability to identify specific patterns and analyze sh

Faceai is a computer vision toolkit designed for facial analysis, identity recognition, and image processing. It provides integrated engines for detecting human faces in static images and live video streams, matching facial encodings against identity databases, and mapping facial landmarks to understand geometric structure and alignment. The project enables real-time augmented reality applications, such as applying virtual makeup and digital accessories by scaling assets to detected facial coordinates. It also includes a suite for digital image restoration capable of removing noise, erasing w

This is a Python facial recognition library designed to detect, encode, and identify human faces in images and video. It functions as a biometric identification tool that converts facial features into numerical encodings to compare and match identities. The library provides a computer vision command line interface for batch processing face detection and recognition tasks across image directories. It also supports a GPU accelerated vision API that utilizes CUDA and NVIDIA hardware to increase the speed of facial analysis and identification. Its capabilities cover human face detection and faci

libfacedetection is a C++ face detection library and computer vision tool. It utilizes a neural network face detector to identify human faces in images and return bounding box coordinates. The library is designed for low latency and high throughput processing, enabling real-time face detection in image and video streams. It supports automated image analysis for identifying coordinates of human faces across large batches of photos and high-performance video processing.

face-api.js is a TensorFlow.js face recognition library and browser-based computer vision API. It provides tools for performing face detection, recognition, and landmark prediction within browsers and Node.js. The library includes a biometric identity descriptor generator that creates numerical vectors to compare identity and similarity between images. It features a facial landmark detection tool for mapping sixty-eight specific coordinate points on a face, as well as an age and gender estimation model. Its capabilities cover real-time facial analysis, including the recognition of facial exp

GoCV is a computer vision library and Go language binding for OpenCV. It serves as an image processing toolkit and deep learning inference engine, providing programmatic access to a wide range of algorithms for image manipulation, object detection, and video analysis. The project differentiates itself through high-performance native bindings and hardware acceleration. It utilizes a foreign function interface to map Go calls to C++ functions and includes a hardware-agnostic backend dispatch to route neural network tasks to computation engines such as CUDA and OpenVINO. The library covers a br

opencv4nodejs is a set of JavaScript wrappers and a C++ native addon that provides Node.js bindings for the OpenCV library. It functions as a computer vision library and image processing framework, exposing high-performance C++ algorithms to a JavaScript environment. The project enables the execution of vision algorithms for detecting faces, tracking objects, and analyzing visual data using deep neural networks. It includes capabilities for data pattern classification, text pattern recognition, and the identification of facial landmarks and gestures. The framework covers a broad capability s

Human is a TensorFlow.js computer vision library used for face, body, and hand tracking within the browser or Node.js. It provides a framework for human pose and gesture tracking, facial recognition, and biometric liveness detection to verify a live human presence. The project distinguishes itself through a full suite of identity and motion tools, including a facial recognition framework that generates embeddings for similarity matching and a background segmenter for separating humans from their environment. It incorporates a liveness detector to prevent spoofing during facial analysis. The

This project is a Go library designed for facial detection, landmark mapping, and identity verification. It provides a toolkit for integrating computer vision capabilities into applications, enabling the automated identification and analysis of human faces within digital images. The library utilizes a deep residual network to transform facial data into compact vector representations, which are then compared using geometric distance calculations to confirm identities. It employs histogram-based object detection to locate facial structures and maps specific points on the face to define geometry

CompreFace is a facial recognition system designed for human face detection, identification, and biometric identity verification. It provides a registry of known people and the ability to match faces in images against this database to determine a specific identity. The system extracts facial landmarks to map geometry and analyzes physical attributes including age, gender, and head pose. It can also verify whether two different images belong to the same individual. The project is implemented as a microservice-based deployment utilizing a REST API gateway and a PostgreSQL metadata store. It in

This project is a collection of neural network models and geometric tools designed for image feature matching, spatial alignment, and visual localization. It provides a pre-trained neural network model for identifying high-accuracy correspondences between sparse image features without requiring local training. The system utilizes a graph neural network matcher that employs attention mechanisms and message passing to learn spatial relationships between image feature points. It integrates a RANSAC camera pose estimator to filter feature matches and calculate the relative spatial transformation

This project is a computer vision framework designed for the detection, identification, and tracking of human subjects within video streams. It provides an integrated system for locating individuals, generating biometric models from image datasets, and maintaining identity labels across consecutive video frames. The system distinguishes itself through its ability to maintain identity persistence across multiple camera feeds. By utilizing deep learning inference to extract feature vector embeddings and applying motion prediction algorithms, it links unique identity signatures across disparate

This project is a Java-based toolkit that integrates the OpenCV computer vision library into the Processing creative coding environment. It provides a programming interface designed to facilitate the inclusion of real-time image analysis and computer vision algorithms within interactive art installations and visual design projects. The library distinguishes itself by wrapping low-level C++ routines into a managed environment, allowing users to perform complex visual tasks through a simplified interface. It supports high-performance operations by sharing raw pixel data between the host environ

This library provides a deep learning framework for identifying human faces and extracting facial landmarks within digital images. It utilizes a multi-task convolutional neural network architecture to simultaneously perform face classification, bounding box regression, and landmark localization. The system processes images through three sequential stages of neural networks, incorporating image pyramid resizing to detect faces of varying scales. To ensure accuracy, it employs bounding box regression to refine coordinate predictions and non-maximum suppression to filter out redundant overlappin

PaddleDetection is an object detection framework designed for the end-to-end development, training, and deployment of computer vision models. It provides a comprehensive library of modular neural network architectures and pipelines that support object detection, instance segmentation, and multi-object tracking tasks. The project distinguishes itself through a configuration-driven approach that decouples model components like backbones and heads, allowing for the flexible assembly of custom vision workflows. It incorporates advanced techniques such as anchor-free detection logic, joint detecti

Rope is a graphical user interface for swapping faces in images and videos. It functions as a deepfake video editor and image face swapper that utilizes pre-trained deep learning models to replace identities in visual media. The tool includes specialized capabilities for AI video post-production, such as occlusion-aware blending to handle foreground objects and mouth-parsing refinement to align facial expressions. It also serves as an AI face restoration tool, using saliency-based restoration to recover clarity and sharpness in swapped facial regions. The software provides a pipeline for vis

Kornia is a differentiable computer vision library and cross-framework tensor vision toolset. It implements vision operations as differentiable tensors to enable integration into deep learning pipelines and supports the transpilation of operations across PyTorch, TensorFlow, JAX, and NumPy. The project provides specialized toolsets for geometric vision and stereo depth, including algorithms for 3D scene reconstruction, camera calibration, and pose estimation. It further distinguishes itself as a differentiable image augmentation framework, applying random geometric and color transformations w

This repository is a comprehensive collection of reference implementations and sample libraries for the Universal Windows Platform. It provides practical examples of how to use Windows Runtime APIs to build cross-device applications, including detailed guidance on XAML-based declarative user interfaces and DirectX-integrated rendering. The project distinguishes itself by providing a wide array of hardware integration suites, covering low-level communication with USB, Serial, I2C, SPI, and GPIO peripherals. It includes specialized implementations for mixed reality holographic rendering, advanc

This project is a JavaScript library designed for real-time face detection directly within a web browser. It functions as a machine learning model wrapper that enables developers to identify and track human faces in live video streams without the need for backend server processing. The library utilizes browser-native media access to stream raw camera data into application memory, where it performs pixel-level analysis. By leveraging a tensor-based inference engine and web-assembly acceleration, the tool executes complex neural network calculations locally to achieve high-performance computer

This project is a collection of optional, community-contributed algorithms and specialized vision tools that extend the core OpenCV framework. It serves as a comprehensive library of extra modules for computer vision research, providing advanced toolsets for image processing, visual data analysis, and object detection. The library includes specialized frameworks for augmented reality tracking, biometric face recognition, and three-dimensional pose estimation. It provides distinct capabilities for identifying AR markers, tracking 3D object silhouettes, and performing neural network vulnerabili

This project is a Python wrapper for the OpenCV computer vision library, providing a bridge that exposes high-performance C++ functions to the Python programming language. It serves as a collection of tools for real-time image processing, object detection, and machine learning on visual data. The project provides precompiled binary distributions, allowing for the integration of vision capabilities into Python applications without requiring a local C++ compiler. It offers multi-variant package distributions, including headless versions designed for server or cloud environments where a graphica

OpenCV is an open-source computer vision library and visual analysis toolkit. It provides a framework for processing static images and dynamic video frames to analyze visual data and extract information using deep learning. The project functions as a real-time image processing framework, enabling the execution of vision algorithms on live video streams for immediate analysis and data processing. The toolkit covers a broad range of capabilities including image pattern recognition, real-time video analysis, and visual data extraction. It also supports automated visual inspection for detecting

JavaCV provides a Java-based interface for native computer vision and video processing libraries. It functions as a wrapper for native vision libraries, allowing Java applications to perform image analysis, object detection, and video stream processing. The project integrates comprehensive computer vision capabilities, including facial recognition, image segmentation, and optical flow analysis for motion tracking. It also provides tools for hardware geometry calibration and projector-camera alignment to ensure accurate spatial representation. The system covers high-performance media renderin

Apache Druid is a real-time analytics database and distributed columnar time-series store designed for sub-second analytical queries. It functions as a data platform featuring a distributed SQL query engine and a real-time data ingestion system for moving historical and streaming data from external sources. The system is distinguished by its ability to provide low-latency analytics under high concurrency to power operational dashboards. It implements a Kerberos-secured environment for user authentication and employs a shared-nothing cluster architecture to enable horizontal scaling. The plat

jetson-inference is a set of libraries and tools for executing optimized deep learning models on embedded GPU hardware. Its primary purpose is to enable real-time computer vision and AI inference at the edge with low latency and high throughput. The project distinguishes itself through high-performance streaming analytics and the ability to execute concurrent AI pipelines on auto-grade silicon. It provides specialized support for multi-sensor stream processing, utilizing zero-copy data transport to load camera frames directly into GPU memory. The codebase covers a broad surface of capabiliti

Howdy is a biometric authentication system for Linux that uses infrared cameras to provide passwordless login and privileged access. It functions as a Pluggable Authentication Module to integrate facial recognition into the standard Linux authentication pipeline. The system relies on near-infrared camera feeds and facial models to verify identity, ignoring visible light interference. Biometric data is stored as encrypted mathematical templates on the local disk to ensure that facial models are not transmitted over a network. The project includes tools for face model management, infrared came