This repository contains a C++ application that demonstrates face recognition capabilities using computer vision techniques. The demo utilizes OpenCV and dlib libraries for efficient face detection and recognition with 3D passive face liveness detection (face anti-spoofing). Key Features: Face detection: The SDK utilizes advanced computer vision techniques to detect faces in images or video frames, enabling a wide range of applications. Face recognition: It can recognize known faces by comparing them with a pre-defined database of individuals. Age estimation: It can estimate the age of detected faces. Gender detection: It can determine the gender of detected faces. Liveness detection: It can detect whether a face is from a live person or a static image.

The MiniAiLive Face Recognition LivenessDetection Server SDK provides system integrators with fast, flexible, and extremely precise facial recognition that can be deployed across various scenarios, including security, access control, public safety, fintech, smart retail, and home protection. The SDK is fully on-premise, meaning all processing happens on the hosting server, and no data leaves the server. The project structure includes bin, cpp, flask, model, python, test_image, and Dockerfile directories. To set up the project on Linux, download the repo, install system dependencies, and copy libraries into the system folder. For Windows, contact MiniAiLive via email. The C++ example involves replacing the license key in main.cpp, building the project, and running it. The Python example requires installing dependencies and running the project. The Python Flask example involves replacing the license key in app.py, installing dependencies, and running the project. The Docker Flask example includes building the docker image and running it. To request a license, contact MiniAiLive. Contributions to the project are welcome by following specific steps. An online demo is available at https://demo.miniai.live. Related products include MiniAI-Face-Recognition-LivenessDetection-AndroidSDK, MiniAI-Face-Recognition-LivenessDetection-iOS-SDK, MiniAI-Face-LivenessDetection-AndroidSDK, MiniAI-Face-LivenessDetection-iOS-SDK, MiniAI-Face-Matching-AndroidSDK, and MiniAI-Face-Matching-iOS-SDK. MiniAiLive is a leading AI solutions company specializing in computer vision and machine learning technologies.

MiniAiLive provides system integrators with fast, flexible and extremely precise facial recognition with 3D passive face liveness detection (face anti-spoofing) that can be deployed across a number of scenarios, including security, access control, public safety, fintech, smart retail and home protection.

NeMo Curator is a GPU-accelerated open-source framework designed for efficient large language model data curation. It provides scalable dataset preparation for tasks like foundation model pretraining, domain-adaptive pretraining, supervised fine-tuning, and parameter-efficient fine-tuning. The library leverages GPUs with Dask and RAPIDS to accelerate data curation, offering customizable and modular interfaces for pipeline expansion and model convergence. Key features include data download, text extraction, quality filtering, deduplication, downstream-task decontamination, distributed data classification, and PII redaction. NeMo Curator is suitable for curating high-quality datasets for large language model training.

CuMo is a project focused on scaling multimodal Large Language Models (LLMs) with Co-Upcycled Mixture-of-Experts. It introduces CuMo, which incorporates Co-upcycled Top-K sparsely-gated Mixture-of-experts blocks into the vision encoder and the MLP connector, enhancing the capabilities of multimodal LLMs. The project adopts a three-stage training approach with auxiliary losses to stabilize the training process and maintain a balanced loading of experts. CuMo achieves comparable performance to other state-of-the-art multimodal LLMs on various Visual Question Answering (VQA) and visual-instruction-following benchmarks.

Refly.AI is an open-source AI-native creation engine that empowers users to transform ideas into production-ready content. It features a free-form canvas interface with multi-threaded conversations, knowledge base integration, contextual memory, intelligent search, WYSIWYG AI editor, and more. Users can leverage AI-powered capabilities, context memory, knowledge base integration, quotes, and AI document editing to enhance their content creation process. Refly offers both cloud and self-hosting options, making it suitable for individuals, enterprises, and organizations. The tool is designed to facilitate human-AI collaboration and streamline content creation workflows.

OmAgent is an open-source agent framework designed to streamline the development of on-device multimodal agents. It enables agents to empower various hardware devices, integrates speed-optimized SOTA multimodal models, provides SOTA multimodal agent algorithms, and focuses on optimizing the end-to-end computing pipeline for real-time user interaction experience. Key features include easy connection to diverse devices, scalability, flexibility, and workflow orchestration. The architecture emphasizes graph-based workflow orchestration, native multimodality, and device-centricity, allowing developers to create bespoke intelligent agent programs.

PowerInfer is a high-speed Large Language Model (LLM) inference engine designed for local deployment on consumer-grade hardware, leveraging activation locality to optimize efficiency. It features a locality-centric design, hybrid CPU/GPU utilization, easy integration with popular ReLU-sparse models, and support for various platforms. PowerInfer achieves high speed with lower resource demands and is flexible for easy deployment and compatibility with existing models like Falcon-40B, Llama2 family, ProSparse Llama2 family, and Bamboo-7B.

RAI is a framework designed to bring general multi-agent system capabilities to robots, enhancing human interactivity, flexibility in problem-solving, and out-of-the-box AI features. It supports multi-modalities, incorporates an advanced database for agent memory, provides ROS 2-oriented tooling, and offers a comprehensive task/mission orchestrator. The framework includes features such as voice interaction, customizable robot identity, camera sensor access, reasoning through ROS logs, and integration with LangChain for AI tools. RAI aims to support various AI vendors, improve human-robot interaction, provide an SDK for developers, and offer a user interface for configuration.

HAMi is a Heterogeneous AI Computing Virtualization Middleware designed to manage Heterogeneous AI Computing Devices in a Kubernetes cluster. It allows for device sharing, device memory control, device type specification, and device UUID specification. The tool is easy to use and does not require modifying task YAML files. It includes features like hard limits on device memory, partial device allocation, streaming multiprocessor limits, and core usage specification. HAMi consists of components like a mutating webhook, scheduler extender, device plugins, and in-container virtualization techniques. It is suitable for scenarios requiring device sharing, specific device memory allocation, GPU balancing, low utilization optimization, and scenarios needing multiple small GPUs. The tool requires prerequisites like NVIDIA drivers, CUDA version, nvidia-docker, Kubernetes version, glibc version, and helm. Users can install, upgrade, and uninstall HAMi, submit tasks, and monitor cluster information. The tool's roadmap includes supporting additional AI computing devices, video codec processing, and Multi-Instance GPUs (MIG).

CRAB is a framework for building LLM agent benchmark environments in a Python-centric way. It is cross-platform and multi-environment, allowing the creation of agent environments supporting various deployment options. The framework offers easy-to-use configuration with the ability to add new actions and define environments seamlessly. CRAB also provides a novel benchmarking suite with tasks and evaluators defined in Python, along with a unique graph evaluator method for detailed metrics.

Mutahunter is an open-source language-agnostic mutation testing tool maintained by CodeIntegrity. It leverages LLM models to inject context-aware faults into codebase, ensuring comprehensive testing. The tool aims to empower companies and developers to enhance test suites and improve software quality by verifying the effectiveness of test cases through creating mutants in the code and checking if the test cases can catch these changes. Mutahunter provides detailed reports on mutation coverage, killed mutants, and survived mutants, enabling users to identify potential weaknesses in their test suites.

Quark Engine is an AI-powered tool designed for analyzing Android APK files. It focuses on enhancing the detection process for auto-suggestion, enabling users to create detection workflows without coding. The tool offers an intuitive drag-and-drop interface for workflow adjustments and updates. Quark Agent, the core component, generates Quark Script code based on natural language input and feedback. The project is committed to providing a user-friendly experience for designing detection workflows through textual and visual methods. Various features are still under development and will be rolled out gradually.

The agent-starter-pack is a collection of production-ready Generative AI Agent templates built for Google Cloud. It accelerates development by providing a holistic, production-ready solution, addressing common challenges in building and deploying GenAI agents. The tool offers pre-built agent templates, evaluation tools, production-ready infrastructure, and customization options. It also provides CI/CD automation and data pipeline integration for RAG agents. The starter pack covers all aspects of agent development, from prototyping and evaluation to deployment and monitoring. It is designed to simplify project creation, template selection, and deployment for agent development on Google Cloud.

Grounded 3D-LLM is a unified generative framework that utilizes referent tokens to reference 3D scenes, enabling the handling of sequences that interleave 3D and textual data. It transforms 3D vision tasks into language formats through task-specific prompts, curating grounded language datasets and employing Contrastive Language-Scene Pre-training (CLASP) to bridge the gap between 3D vision and language models. The model covers tasks like 3D visual question answering, dense captioning, object detection, and language grounding.

Daydreams is a generative agent library designed for playing onchain games by injecting context. It is chain agnostic and allows users to perform onchain tasks, including playing any onchain game. The tool is lightweight and powerful, enabling users to define game context, register actions, set goals, monitor progress, and integrate with external agents. Daydreams aims to be 'lite' and 'composable', dynamically generating code needed to play games. It is currently in pre-alpha stage, seeking feedback and collaboration for further development.

AI-powered 3D Face Detection & Rotation Tracking, Face Description & Recognition, Body Pose Tracking, 3D Hand & Finger Tracking, Iris Analysis, Age & Gender & Emotion Prediction, Gaze Tracking, Gesture Recognition, Body Segmentation

This repository contains a C++ application that demonstrates face recognition capabilities using computer vision techniques. The demo utilizes OpenCV and dlib libraries for efficient face detection and recognition with 3D passive face liveness detection (face anti-spoofing). Key Features: Face detection: The SDK utilizes advanced computer vision techniques to detect faces in images or video frames, enabling a wide range of applications. Face recognition: It can recognize known faces by comparing them with a pre-defined database of individuals. Age estimation: It can estimate the age of detected faces. Gender detection: It can determine the gender of detected faces. Liveness detection: It can detect whether a face is from a live person or a static image.

FaceAPI is an AI-powered tool for face detection, rotation tracking, face description, recognition, age, gender, and emotion prediction. It can be used in both browser and NodeJS environments using TensorFlow/JS. The tool provides live demos for processing images and webcam feeds, along with NodeJS examples for various tasks such as face similarity comparison and multiprocessing. FaceAPI offers different pre-built versions for client-side browser execution and server-side NodeJS execution, with or without TFJS pre-bundled. It is compatible with TFJS 2.0+ and TFJS 3.0+.

MiKaPo is a web-based tool that allows users to pose MMD models in real-time using video input. It utilizes technologies such as Mediapipe for 3D key points detection, Babylon.js for 3D scene rendering, babylon-mmd for MMD model viewing, and Vite+React for the web framework. Users can upload videos and images, select different environments, and choose models for posing. MiKaPo also supports camera input and Ollama (electron version). The tool is open to feature requests and pull requests, with ongoing development to add VMD export functionality.

DeepSparkHub is a repository that curates hundreds of application algorithms and models covering various fields in AI and general computing. It supports mainstream intelligent computing scenarios in markets such as smart cities, digital individuals, healthcare, education, communication, energy, and more. The repository provides a wide range of models for tasks such as computer vision, face detection, face recognition, instance segmentation, image generation, knowledge distillation, network pruning, object detection, 3D object detection, OCR, pose estimation, self-supervised learning, semantic segmentation, super resolution, tracking, traffic forecast, GNN, HPC, methodology, multimodal, NLP, recommendation, reinforcement learning, speech recognition, speech synthesis, and 3D reconstruction.

FaceAiSharp is a .NET library designed for face-related computer vision tasks. It offers functionalities such as face detection, face recognition, facial landmarks detection, and eye state detection. The library utilizes pretrained ONNX models for accurate and efficient results, enabling users to integrate these capabilities into their .NET applications easily. With a focus on simplicity and performance, FaceAiSharp provides a local processing solution without relying on cloud services, supporting image-based face processing using ImageSharp. It is cross-platform compatible, supporting Windows, Linux, Android, and more.

VisionCamera is a powerful, high-performance Camera library for React Native. It features Photo and Video capture, QR/Barcode scanner, Customizable devices and multi-cameras ("fish-eye" zoom), Customizable resolutions and aspect-ratios (4k/8k images), Customizable FPS (30..240 FPS), Frame Processors (JS worklets to run facial recognition, AI object detection, realtime video chats, ...), Smooth zooming (Reanimated), Fast pause and resume, HDR & Night modes, Custom C++/GPU accelerated video pipeline (OpenGL).

Viseron is a self-hosted, local-only NVR and AI computer vision software that provides features such as object detection, motion detection, and face recognition. It allows users to monitor their home, office, or any other place they want to keep an eye on. Getting started with Viseron is easy by spinning up a Docker container and editing the configuration file using the built-in web interface. The software's functionality is enabled by components, which can be explored using the Component Explorer. Contributors are welcome to help with implementing open feature requests, improving documentation, and answering questions in issues or discussions. Users can also sponsor Viseron or make a one-time donation.

ChatFAQ is an open-source comprehensive platform for creating a wide variety of chatbots: generic ones, business-trained, or even capable of redirecting requests to human operators. It includes a specialized NLP/NLG engine based on a RAG architecture and customized chat widgets, ensuring a tailored experience for users and avoiding vendor lock-in.

AnythingLLM is a full-stack application that enables you to turn any document, resource, or piece of content into context that any LLM can use as references during chatting. This application allows you to pick and choose which LLM or Vector Database you want to use as well as supporting multi-user management and permissions.

Chatbot UI is an open-source AI chat app that allows users to create and deploy their own AI chatbots. It is easy to use and can be customized to fit any need. Chatbot UI is perfect for businesses, developers, and anyone who wants to create a chatbot.

Deep Chat is a fully customizable AI chat component that can be injected into your website with minimal to no effort. Whether you want to create a chatbot that leverages popular APIs such as ChatGPT or connect to your own custom service, this component can do it all! Explore deepchat.dev to view all of the available features, how to use them, examples and more!

Avalonia-Assistant is an open-source desktop intelligent assistant that aims to provide a user-friendly interactive experience based on the Avalonia UI framework and the integration of Semantic Kernel with OpenAI or other large LLM models. By utilizing Avalonia-Assistant, you can perform various desktop operations through text or voice commands, enhancing your productivity and daily office experience.

ChatGPT Web is a web application that provides access to the ChatGPT API. It offers two non-official methods to interact with ChatGPT: through the ChatGPTAPI (using the `gpt-3.5-turbo-0301` model) or through the ChatGPTUnofficialProxyAPI (using a web access token). The ChatGPTAPI method is more reliable but requires an OpenAI API key, while the ChatGPTUnofficialProxyAPI method is free but less reliable. The application includes features such as user registration and login, synchronization of conversation history, customization of API keys and sensitive words, and management of users and keys. It also provides a user interface for interacting with ChatGPT and supports multiple languages and themes.

Tiledesk is an open-source live chat platform with integrated chatbots written in Node.js and Express. It is designed to be a multi-channel platform for web, Android, and iOS, and it can be used to increase sales or provide post-sales customer service. Tiledesk's chatbot technology allows for automation of conversations, and it also provides APIs and webhooks for connecting external applications. Additionally, it offers a marketplace for apps and features such as CRM, ticketing, and data export.

UFO is a UI-focused dual-agent framework to fulfill user requests on Windows OS by seamlessly navigating and operating within individual or spanning multiple applications.