Awesome GitHub RepositoriesFace Embeddings

PhotoPrism is a self-hosted digital asset management platform designed to organize, classify, and manage large collections of photos and videos on personal infrastructure. It functions as a private alternative to cloud-based services, ensuring that all media remains under the user's control. The platform utilizes neural-network-based media analysis to automatically detect objects, faces, and locations, providing a comprehensive, AI-powered approach to library organization. The project distinguishes itself through its containerized architecture, which simplifies deployment and lifecycle manage

Deepface is a comprehensive deep learning library for facial recognition and demographic analysis. It provides a modular pipeline that handles the entire lifecycle of facial processing, including detection, geometric alignment, and the transformation of facial images into high-dimensional numerical vector embeddings for identity verification and similarity comparison. The library distinguishes itself through a model ensemble approach, which combines predictions from multiple pre-trained neural networks to improve classification accuracy and reduce bias. It also integrates advanced security fe

FaceNet is a facial recognition framework designed to transform facial images into high-dimensional numerical embeddings for identity verification and recognition. It provides a deep learning face embedder that maps facial features into a Euclidean space where distance corresponds to facial similarity. The system includes tools for both supervised and unsupervised identity management. It features a face identity classifier for categorizing images into known identity classes and an unsupervised clustering tool to group similar facial embeddings together without predefined labels. The framewor

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

lite.ai.toolkit एज AI तैनाती के लिए डिज़ाइन किया गया एक C++ कंप्यूटर विज़न टूलकिट है। यह संसाधन-सीमित उपकरणों पर ऑब्जेक्ट डिटेक्शन, इमेज क्लासिफिकेशन और सेगमेंटेशन के लिए प्री-ट्रेंड मॉडल के निष्पादन को सक्षम बनाता है। इस प्रोजेक्ट में एक मल्टी-बैकएंड इन्फरेंस इंजन है जो ONNX मॉडल रनटाइम का समर्थन करता है, जिससे AI मॉडल को विभिन्न हार्डवेयर लक्ष्यों पर चलने की अनुमति मिलती है। इसमें लेटेंसी को कम करने और प्रोसेसिंग गति बढ़ाने के लिए विशेष रूप से NVIDIA हार्डवेयर के लिए एक GPU-त्वरित पाइपलाइन शामिल है। यह टूलकिट चेहरे के विश्लेषण की क्षमताओं की एक विस्तृत श्रृंखला को कवर करता है, जिसमें भावना पहचान, लिंग और आयु अनुमान और हेड पोज़ विश्लेषण शामिल है। यह फीचर एम्बेडिंग के निष्कर्षण और पहचान को सत्यापित करने के लिए कोसाइन समानता की गणना के माध्यम से चेहरे की पहचान के लिए उपकरण भी प्रदान करता। अतिरिक्त क्षमताओं में फोरग्राउंड आइसोलेशन के लिए इमेज मैटिंग, ग्रेस्केल इमेज कलराइज़ेशन और आर्टिस्टिक स्टाइल ट्रांसफर शामिल हैं।

face.evoLVe is a deep learning library designed for the training and deployment of facial recognition models. It provides a comprehensive framework for converting facial images into numerical feature vectors, enabling identity verification and similarity analysis across large-scale datasets. The project facilitates the entire lifecycle of facial analysis, from dataset preparation and image standardization to distributed model training. It includes utilities for detecting facial landmarks and applying geometric transformations to ensure consistent input orientation, as well as data augmentatio

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