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Showing 1560 open source projects for "dev-c"
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ACI Learning: Internal Audit, Cybersecurity, and IT TrainingTraditional training doesn't equip employees with the practical skills they need to drive business success. ACI Learning provides hands-on IT and cybersecurity training designed to build real-world, on-the-job skills. Our outcome-based programs empower employees with certification prep, industry-recognized credentials, and flexible learning options. With expert-led video training, labs, and scalable solutions, we help businesses, individuals, governments, and academic institutions develop a skilled workforce, align with business goals, and stay ahead in a rapidly evolving digital world.
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Your go-to FinOps platformUnlike reporting-only FinOps tools, FinOpsly unifies cloud (AWS, Azure, GCP), data (Snowflake, Databricks, BigQuery), and AI costs into a single system of action — enabling teams to plan spend before it happens, automate optimization safely, and prove value in weeks, not quarters.
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LearnOpenCV
C++ and Python Examples
LearnOpenCV is a large educational repository that provides practical computer vision and deep learning examples in both Python and C++. The project accompanies the LearnOpenCV blog and contains hundreds of hands-on tutorials covering topics such as object detection, image processing, pose estimation, and neural networks. It is structured as a learning resource where each directory corresponds to a specific article or technical walkthrough. The repository supports beginners and advanced practitioners by offering reproducible code that demonstrates real-world computer vision techniques. ... -
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OpenWhip
Optimize interaction with AI coding assistants
...The application runs as a lightweight system tray program and overlays a visual whip animation on the screen when activated, creating an interactive and slightly absurd interface for user engagement. Its core functionality is surprisingly practical beneath the joke: when triggered, it sends a keyboard interrupt signal (Ctrl+C) to halt the current AI process, effectively giving developers a quick way to stop unresponsive or slow-running tasks. In addition to the interrupt, the tool also delivers randomized “encouraging” or humorous messages, blending utility with personality and making the experience more entertaining. -
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DeepGEMM
Clean and efficient FP8 GEMM kernels with fine-grained scaling
DeepGEMM is a specialized CUDA library for efficient, high-performance general matrix multiplication (GEMM) operations, with particular focus on low-precision formats such as FP8 (and experimental support for BF16). The library is designed to work cleanly and simply, avoiding overly templated or heavily abstracted code, while still delivering performance that rivals expert-tuned libraries. It supports both standard and “grouped” GEMMs, which is useful for architectures like Mixture of... -
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AlphaFold 3
AlphaFold 3 inference pipeline
AlphaFold 3, developed by Google DeepMind, is an advanced deep learning system for predicting biomolecular structures and interactions with exceptional accuracy. This repository provides the complete inference pipeline for running AlphaFold 3, though access to the model parameters is restricted and must be obtained directly from Google under specific terms of use. The system is designed for scientific research applications in structural biology, biochemistry, and bioinformatics, enabling... -
Powerful Website Security | Continuous Web Threat PlatformReflectiz is a comprehensive web exposure management platform that helps organizations proactively identify, monitor, and mitigate security, privacy, and compliance risks across their online environments. Designed to address the growing complexity of modern websites, Reflectiz provides full visibility and control over first, third, and even fourth-party components, such as scripts, trackers, and open-source libraries that often evade traditional security tools.
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IREE
A retargetable MLIR-based machine learning compiler runtime toolkit
IREE (Intermediate Representation Execution Environment, pronounced as "eerie") is an MLIR-based end-to-end compiler and runtime that lowers Machine Learning (ML) models to a unified IR that scales up to meet the needs of the data center and down to satisfy the constraints and special considerations of mobile and edge deployments. -
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TEN
Open-source framework for conversational voice AI agents
...It includes a full ecosystem, TEN Turn Detection, TEN Agent, and TMAN Designer, allowing developers to rapidly assemble human-like, responsive agents that can see, speak, hear, and interact. With support for languages like Python, C++, and Go, it offers flexible deployment on both edge and cloud environments. Using components like graph-based workflow design, drag-and-drop UI (via TMAN Designer), and reusable extensions such as real-time avatars, RAG (Retrieval-Augmented Generation), and image generation, TEN enables highly customizable, scalable agent development with minimal code. -
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DeepDetect
Deep Learning API and Server in C++14 support for Caffe, PyTorch
...Training in a few hours and with small data thanks to 25+ pre-trained models. Full Open Source, with an ecosystem of tools (API clients, video, annotation, ...) Fast Server written in pure C++, a single codebase for Cloud, Desktop & Embedded. -
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OceanBase seekdb
The AI-Native Search Database
seekdb is an AI-native search database from OceanBase that unifies vector, full-text, relational, JSON, and GIS data into a single query engine. The system is designed to support hybrid search workloads and in-database AI workflows without requiring multiple specialized databases. It enables developers to perform semantic search, keyword search, and structured SQL queries within the same platform, simplifying modern AI application stacks. seekdb also embeds AI capabilities directly in the... -
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Distributed Llama
Connect home devices into a powerful cluster to accelerate LLM
Distributed Llama is an open-source project that enables users to connect multiple home devices into a powerful cluster to accelerate Large Language Model (LLM) inference. By leveraging tensor parallelism and high-speed synchronization over Ethernet, it allows for faster performance as more devices are added to the cluster. The system supports various operating systems, including Linux, macOS, and Windows, and is optimized for both ARM and x86_64 AVX2 CPUs. -
Composable, Open Source Payments PlatformJuspay's Payments Orchestration Platform offers a comprehensive product suite for businesses, including open-source payment orchestration, global payouts, seamless authentication, payment tokenization, fraud & risk management, end-to-end reconciliation, unified payment analytics & more. The company’s offerings also include end-to-end white label payment gateway solutions & real-time payments infrastructure for banks. These solutions help businesses achieve superior conversion rates, reduce fraud, optimize costs, and deliver seamless customer experiences at scale.
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Unity MCP
AI-powered bridge connecting LLMs and advanced AI agents
Unity-MCP is an open-source integration that connects artificial intelligence assistants with the Unity game development environment through the Model Context Protocol. The project enables AI tools such as coding assistants and autonomous agents to interact directly with Unity projects, allowing them to analyze scenes, modify assets, and generate code within the development environment. By exposing Unity editor functionality through MCP tools, the plugin allows external AI systems to... -
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5ire
5ire is a cross-platform desktop AI assistant, MCP client
...If you don't anticipate using the tools feature immediately, you may choose to skip this installation step and complete it later when the need arises. MCP is an open protocol that standardizes how applications provide context to LLMs. Think of MCP like a USB-C port for AI applications. Just as USB-C provides a standardized way to connect your devices to various peripherals and accessories, MCP provides a standardized way to connect AI models to different data sources and tools. -
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MNN
MNN is a blazing fast, lightweight deep learning framework
MNN is a highly efficient and lightweight deep learning framework. It supports inference and training of deep learning models, and has industry leading performance for inference and training on-device. At present, MNN has been integrated in more than 20 apps of Alibaba Inc, such as Taobao, Tmall, Youku, Dingtalk, Xianyu and etc., covering more than 70 usage scenarios such as live broadcast, short video capture, search recommendation, product searching by image, interactive marketing, equity... -
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dlib
Toolkit for making machine learning and data analysis applications
Dlib is a modern C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems. It is used in both industry and academia in a wide range of domains including robotics, embedded devices, mobile phones, and large high performance computing environments. Dlib's open source licensing allows you to use it in any application, free of charge. -
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OllamaSharp
The easiest way to use Ollama in .NET
OllamaSharp is an open-source .NET library that provides strongly typed bindings for interacting with the Ollama API, making it easier for developers to integrate local large language models into C# and .NET applications. The project acts as a wrapper around the Ollama API, exposing all endpoints through asynchronous methods that allow developers to perform tasks such as generating text, creating embeddings, and managing models. It supports both local and remote Ollama instances, enabling developers to run AI models on their own hardware or connect to remote model servers. ... -
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bitnet.cpp
Official inference framework for 1-bit LLMs
bitnet.cpp is the official open-source inference framework and ecosystem designed to enable ultra-efficient execution of 1-bit large language models (LLMs), which quantize most model parameters to ternary values (-1, 0, +1) while maintaining competitive performance with full-precision counterparts. At its core is bitnet.cpp, a highly optimized C++ backend that supports fast, low-memory inference on both CPUs and GPUs, enabling models such as BitNet b1.58 to run without requiring enormous compute infrastructure. The project’s focus on extreme quantization dramatically reduces memory footprint and energy consumption compared with traditional 16-bit or 32-bit LLMs, making it practical to deploy advanced language understanding and generation models on everyday machines. ... -
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Torch-TensorRT
PyTorch/TorchScript/FX compiler for NVIDIA GPUs using TensorRT
Torch-TensorRT is a compiler for PyTorch/TorchScript, targeting NVIDIA GPUs via NVIDIA’s TensorRT Deep Learning Optimizer and Runtime. Unlike PyTorch’s Just-In-Time (JIT) compiler, Torch-TensorRT is an Ahead-of-Time (AOT) compiler, meaning that before you deploy your TorchScript code, you go through an explicit compile step to convert a standard TorchScript program into a module targeting a TensorRT engine. Torch-TensorRT operates as a PyTorch extension and compiles modules that integrate... -
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openpilot
Open source driver assistance system
openpilot is an open-source driver assistance system designed to improve upon the existing driver assistance of most modern cars today. openpilot gives you Tesla Autopilot-like functionality with functions like Adaptive Cruise Control (ACC), Automated Lane Centering (ALC), Forward Collision Warning (FCW) and Lane Departure Warning (LDW). All these with just a push of a button. openpilot also includes a camera-based driver monitoring feature that alerts distracted and asleep drivers while it... -
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NVIDIA cuOpt
GPU accelerated decision optimization
...It supports a range of optimization models including linear programming (LP), mixed integer linear programming (MILP), quadratic programming (QP), and vehicle routing problems (VRP). Built primarily in C++, cuOpt leverages NVIDIA GPUs to deliver near real-time solutions for optimization tasks involving millions of variables and constraints. The platform provides multiple interfaces, including C, Python, and server APIs, allowing developers to integrate optimization capabilities into applications and services. cuOpt is designed for high-performance environments and can be deployed across cloud, hybrid, or on-premise infrastructures. ... -
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fairseq2
FAIR Sequence Modeling Toolkit 2
fairseq2 is a modern, modular sequence modeling framework developed by Meta AI Research as a complete redesign of the original fairseq library. Built from the ground up for scalability, composability, and research flexibility, fairseq2 supports a broad range of language, speech, and multimodal content generation tasks, including instruction fine-tuning, reinforcement learning from human feedback (RLHF), and large-scale multilingual modeling. Unlike the original fairseq—which evolved into a... -
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CatBoost
High-performance library for gradient boosting on decision trees
CatBoost is a fast, high-performance open source library for gradient boosting on decision trees. It is a machine learning method with plenty of applications, including ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. CatBoost offers superior performance over other GBDT libraries on many datasets, and has several superb features. It has best in class prediction speed, supports both numerical and categorical features, has a fast and scalable GPU version, and readily comes with visualization tools. CatBoost was developed by Yandex and is used in various areas including search, self-driving cars, personal assistance, weather prediction and more. -
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The Arcade Learning Environment
The Arcade Learning Environment (ALE) -- a platform for AI research
Arcade Learning Environment (ALE) is a widely used open-source framework that wraps hundreds of Atari 2600 games via an emulator and presents them as RL environments for AI agents. It decouples the game/emulation aspects from the agent interface, providing a clean API (C++, Python, Gymnasium) so researchers can focus on agent design rather than game plumbing. This environment suite has been central to many RL breakthroughs, including value-based agents, deep Q-nets, and general-agent benchmarking, because the Atari games span many genres and present diverse learning challenges (pixels, actions, delayed rewards). ... -
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Everywhere
Context-aware desktop AI assistant that understands screen content
Everywhere is a context-aware desktop AI assistant designed to interact directly with the content displayed on a user’s screen. It distinguishes itself from traditional AI tools by eliminating the need for manual input methods such as copying text or taking screenshots, instead allowing users to invoke assistance instantly through a shortcut. It can analyze on-screen information in real time and provide contextual responses, making it useful for tasks like troubleshooting errors, summarizing... -
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Simd Library
C++ image processing and machine learning library with using of SIMD
...In particular, the library supports the following CPU extensions: SSE, AVX, AVX-512, and AMX for x86/x64, and NEON for ARM. The Simd Library has C API and also contains useful C++ classes and functions to facilitate access to C API. The library supports dynamic and static linking, 32-bit and 64-bit Windows and Linux, MSVS, G++ and Clang compilers, MSVS projects, and CMake build systems. -
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DragonianVoice
C++ inference library for multiple SVC/TTS
DragonianVoice is a C++ inference library that unifies multiple speech synthesis, voice conversion, and singing voice synthesis models under a single, high-performance ONNX-based framework. It focuses on being a reusable native library rather than a full UI product, with bindings for C, C++, and C# so it can be embedded into other applications or engines. -
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Diplomacy Cicero
Code for Cicero, an AI agent that plays the game of Diplomacy
...It supports two variants: Cicero (which handles full “press” negotiation) and Diplodocus (a variant focused on no-press diplomacy) as described in the README. The codebase is implemented primarily in Python with performance-critical components in C++ (via pybind11 bindings) and is configured to run in a high‐GPU cluster environment. Configuration is managed via protobuf files to define tasks such as self-play, benchmark agent comparisons, and RL training. The project is now archived and read-only, reflecting that it is no longer actively developed but remains publicly available for research use.
