Open Source C++ Artificial Intelligence Software
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C++ Artificial Intelligence Software
View 15508 business solutionsBrowse free open source C++ Artificial Intelligence Software and projects below. Use the toggles on the left to filter open source C++ Artificial Intelligence Software by OS, license, language, programming language, and project status.
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
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Tesseract OCR
Open Source OCR Engine
Tesseract is an open source OCR or optical character recognition engine and command line program. OCR is a technology that allows for the recognition of text characters within a digital image. With the latest version of Tesseract, there is a greater focus on line recognition, however it still supports the legacy Tesseract OCR engine which recognizes character patterns. Tesseract can recognize over 100 languages out-of-the-box, and can be trained to recognize other languages. It supports various output formats, including plain text, HTML, PDF and more. It also has unicode (UTF-8) support. -
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OpenCV
Open Source Computer Vision Library
The Open Source Computer Vision Library has >2500 algorithms, extensive documentation and sample code for real-time computer vision. It works on Windows, Linux, Mac OS X, Android, iOS in your browser through JavaScript. Languages: C++, Python, Julia, Javascript Homepage: https://opencv.org Q&A forum: https://forum.opencv.org/ Documentation: https://docs.opencv.org Source code: https://github.com/opencv Please pay special attention to our tutorials! https://docs.opencv.org/master Books about the OpenCV are described here: https://opencv.org/books.html -
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whisper.cpp
Port of OpenAI's Whisper model in C/C++
whisper.cpp is a lightweight, C/C++ reimplementation of OpenAI’s Whisper automatic speech recognition (ASR) model—designed for efficient, standalone transcription without external dependencies. The entire high-level implementation of the model is contained in whisper.h and whisper.cpp. The rest of the code is part of the ggml machine learning library. The command downloads the base.en model converted to custom ggml format and runs the inference on all .wav samples in the folder samples. whisper.cpp supports integer quantization of the Whisper ggml models. Quantized models require less memory and disk space and depending on the hardware can be processed more efficiently. -
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Operit AI
Powerful Android AI agent with tools, automation, and Linux shell
Operit is a full-featured AI assistant and agent platform designed specifically for Android devices, aiming to go far beyond traditional chat-based interfaces. It integrates deep system-level capabilities with a wide range of tools, allowing the AI to perform real tasks such as file management, automation, and system control directly on the device. A standout aspect of the project is its built-in Ubuntu 24 environment, which enables users to run Linux commands, scripts, and development tools in a mobile context. Operit supports both local and remote AI models, including offline execution through frameworks like llama.cpp and MNN, helping preserve user privacy while maintaining flexibility. Operit also includes an intelligent memory system that stores, organizes, and retrieves user interactions to provide more personalized and context-aware responses. In addition, it offers workflow automation, plugin extensibility, & a rich tool ecosystem, making it suitable for advanced productivity. -
Save Up to 91% on Cloud Compute With Spot VMsRun batch jobs at 60-91% off with Spot VMs. Long-running workloads get automatic discounts with sustained use.
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Piper TTS
A fast, local neural text to speech system
Piper is a fast, local neural text-to-speech (TTS) system developed by the Rhasspy team. Optimized for devices like the Raspberry Pi 4, Piper enables high-quality speech synthesis without relying on cloud services, making it ideal for privacy-conscious applications. It utilizes ONNX models trained with VITS to deliver natural-sounding voices across various languages and accents. Piper is particularly suited for offline voice assistants and embedded systems. -
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Capture2Text
Quickly OCR part of the screen and save resulting text to clipboard
Capture2Text enables users to quickly OCR a portion of the screen using a keyboard shortcut. The resulting text will be saved to the clipboard by default. Supports 90+ languages including Chinese, English, French, German, Japanese, Korean, Russian, and Spanish. Portable and does not require installation. See http://capture2text.sourceforge.net for details. -
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Text to Speech engine for English and many other languages. Compact size with clear but artificial pronunciation. Available as a command-line program with many options, a shared library for Linux, and a Windows SAPI5 version.
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XiaoZhi AI Chatbot
Build your own AI friend
xiaozhi-esp32 is an open-source project that guides users in building their own AI-powered conversational companion using the ESP32 microcontroller. The project provides detailed instructions on assembling the hardware, setting up the software, and integrating AI models to enable natural language interactions. This DIY approach offers an accessible entry point into AI and hardware development. -
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sherpa-onnx
Speech-to-text, text-to-speech, and speaker recognition
Speech-to-text, text-to-speech, and speaker recognition using next-gen Kaldi with onnxruntime without an Internet connection. Support embedded systems, Android, iOS, Raspberry Pi, RISC-V, x86_64 servers, websocket server/client, C/C++, Python, Kotlin, C#, Go, NodeJS, Java, Swift, Dart, JavaScript, Flutter. -
Go from Code to Production URL in SecondsSkip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
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GPT4All
Run Local LLMs on Any Device. Open-source
GPT4All is an open-source project that allows users to run large language models (LLMs) locally on their desktops or laptops, eliminating the need for API calls or GPUs. The software provides a simple, user-friendly application that can be downloaded and run on various platforms, including Windows, macOS, and Ubuntu, without requiring specialized hardware. It integrates with the llama.cpp implementation and supports multiple LLMs, allowing users to interact with AI models privately. This project also supports Python integrations for easy automation and customization. GPT4All is ideal for individuals and businesses seeking private, offline access to powerful LLMs. -
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NeuralNote
Audio Plugin for Audio to MIDI transcription using deep learning
NeuralNote is an open-source audio software tool designed to convert recorded audio into MIDI data using modern machine learning techniques. The software functions as an audio plugin that can be used inside digital audio workstations as well as a standalone application for music production and analysis. Its main purpose is to perform audio-to-MIDI transcription, allowing musicians to record a performance and automatically transform it into editable MIDI notes. NeuralNote supports polyphonic transcription, meaning it can detect multiple notes played simultaneously, making it useful for instruments such as piano or guitar. The system relies on neural network models to analyze audio signals and infer pitch, timing, and other musical attributes that can be represented as MIDI data. The resulting MIDI output can be edited, quantized, or exported to other instruments within a music production workflow. -
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The main purpose of this program is to provide functionality for extract hardcoded subtitles (hardsub) from video. It provides two main features: 1) Autodetection of frames with hardcoded text (hardsub) on video with saving info about timing positions. 2) Generation of cleared from background text images, which allows with usage of OCR programs (like FineReader, Subtitle Edit, Google Drive) to generate complete subtitles with original text and timing. For working of this program on Windows will be required "Microsoft Visual C++ Redistributable runtime libraries 2022": https://support.microsoft.com/en-us/help/2977003/the-latest-supported-visual-c-downloads Latest versions were built and tested on: Windows 10 x64, Ubuntu 20.04.5 LTS, openSUSE Leap 15.4, Arch Linux (EndeavourOS Cassini Nova 03-2023) For faster support in case of bug fixes please contact me in: https://vk.com/skosnits For donate: https://sourceforge.net/projects/videosubfinder/donate
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MeCab is a fast and customizable Japanese morphological analyzer. MeCab is designed for generic purpose and applied to variety of NLP tasks, such as Kana-Kanji conversion. MeCab provides parameter estimation functionalities based on CRFs and HMM
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llama.cpp
Port of Facebook's LLaMA model in C/C++
The llama.cpp project enables the inference of Meta's LLaMA model (and other models) in pure C/C++ without requiring a Python runtime. It is designed for efficient and fast model execution, offering easy integration for applications needing LLM-based capabilities. The repository focuses on providing a highly optimized and portable implementation for running large language models directly within C/C++ environments. -
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Armadillo
fast C++ library for linear algebra & scientific computing
* Fast C++ library for linear algebra (matrix maths) and scientific computing * Easy to use functions and syntax, deliberately similar to Matlab / Octave * Uses template meta-programming techniques to increase efficiency * Provides user-friendly wrappers for OpenBLAS, Intel MKL, LAPACK, ATLAS, ARPACK, SuperLU and FFTW libraries * Useful for machine learning, pattern recognition, signal processing, bioinformatics, statistics, finance, etc. * Downloads: http://arma.sourceforge.net/download.html * Documentation: http://arma.sourceforge.net/docs.html * Bug reports: http://arma.sourceforge.net/faq.html * Git repo: https://gitlab.com/conradsnicta/armadillo-code -
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PaddleOCR
Awesome multilingual OCR toolkits based on PaddlePaddle
PaddleOCR offers exceptional, multilingual, and practical Optical Character Recognition (OCR) tools that can help users train better models and apply them into practice. Inspired by PaddlePaddle, PaddleOCR is an ultra lightweight OCR system, with multilingual recognition, digit recognition, vertical text recognition, as well as long text recognition. It features a PPOCR series of high-quality pre-trained models, which includes: ultra lightweight ppocr_mobile series models, general ppocr_server series models, and ultra lightweight compression ppocr_mobile_slim series models. PaddleOCR is easy to install and easy to use on Windows, Linux, MacOS and other systems. -
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llamafile
Distribute and run LLMs with a single file
llamafile lets you distribute and run LLMs with a single file. (announcement blog post). Our goal is to make open LLMs much more accessible to both developers and end users. We're doing that by combining llama.cpp with Cosmopolitan Libc into one framework that collapses all the complexity of LLMs down to a single-file executable (called a "llamafile") that runs locally on most computers, with no installation. The easiest way to try it for yourself is to download our example llamafile for the LLaVA model (license: LLaMA 2, OpenAI). LLaVA is a new LLM that can do more than just chat; you can also upload images and ask it questions about them. With llamafile, this all happens locally; no data ever leaves your computer. -
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Vosk Speech Recognition Toolkit
Offline speech recognition API for Android, iOS, Raspberry Pi
Vosk is an offline open source speech recognition toolkit. It enables speech recognition for 20+ languages and dialects - English, Indian English, German, French, Spanish, Portuguese, Chinese, Russian, Turkish, Vietnamese, Italian, Dutch, Catalan, Arabic, Greek, Farsi, Filipino, Ukrainian, Kazakh, Swedish, Japanese, Esperanto, Hindi, Czech, Polish. More to come. Vosk models are small (50 Mb) but provide continuous large vocabulary transcription, zero-latency response with streaming API, reconfigurable vocabulary and speaker identification. Speech recognition bindings are implemented for various programming languages like Python, Java, Node.JS, C#, C++, Rust, Go and others. Vosk supplies speech recognition for chatbots, smart home appliances, and virtual assistants. It can also create subtitles for movies, and transcription for lectures and interviews. Vosk scales from small devices like Raspberry Pi or Android smartphones to big clusters. -
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Screen Translator
Screen capture, OCR and translation tool
This software allows you to translate any text on screen. Basically it is a combination of screen capture, OCR and translation tools. More info and the latest release on the homepage (https://github.com/OneMoreGres/ScreenTranslator) -
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stable-diffusion.cpp
Diffusion model(SD,Flux,Wan,Qwen Image,Z-Image,...) inference
stable-diffusion.cpp is a lightweight, high-performance implementation of Stable Diffusion and related generative models written entirely in portable C/C++, designed to run on virtually any device without heavy dependencies. It enables text-to-image and image-to-image generation, supports a growing set of models like SD1.x, SD2.x, SDXL, SD-Turbo, Qwen Image, and more, and is continually updated with support for cutting-edge model variants including video and image editing models. The project is built on the ggml backend, which allows efficient execution on CPUs and GPUs via backends like CUDA, Vulkan, Metal, OpenCL, and SYCL, making it suitable for everything from desktops to mobile devices. It includes options for ControlNet, LoRA models, upscaling via ESRGAN, and advanced sampling techniques, giving developers and users a rich toolkit for creative workflows. -
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OpenCV
Open Source Computer Vision Library
OpenCV (Open Source Computer Vision Library) is a comprehensive open-source library for computer vision, machine learning, and image processing. It enables developers to build real-time vision applications ranging from facial recognition to object tracking. OpenCV supports a wide range of programming languages including C++, Python, and Java, and is optimized for both CPU and GPU operations. -
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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 distribution, security risk control. In addition, MNN is also used on embedded devices, such as IoT. MNN Workbench could be downloaded from MNN's homepage, which provides pretrained models, visualized training tools, and one-click deployment of models to devices. Android platform, core so size is about 400KB, OpenCL so is about 400KB, Vulkan so is about 400KB. Supports hybrid computing on multiple devices. Currently supports CPU and GPU. -
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Hunspell is a spell checker and morphological analyzer library and program designed for languages with rich morphology and complex compounding or character encoding. Hunspell interfaces: Curses, Ispell compatible pipe interface, OpenOffice.org UNO module
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COLMAP
Structure-from-Motion and Multi-View Stereo
COLMAP is a general-purpose Structure-from-Motion (SfM) and Multi-View Stereo (MVS) pipeline with a graphical and command-line interface. It offers a wide range of features for the reconstruction of ordered and unordered image collections. The software is licensed under the new BSD license. -
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ONNX Runtime
ONNX Runtime: cross-platform, high performance ML inferencing
ONNX Runtime is a cross-platform inference and training machine-learning accelerator. ONNX Runtime inference can enable faster customer experiences and lower costs, supporting models from deep learning frameworks such as PyTorch and TensorFlow/Keras as well as classical machine learning libraries such as scikit-learn, LightGBM, XGBoost, etc. ONNX Runtime is compatible with different hardware, drivers, and operating systems, and provides optimal performance by leveraging hardware accelerators where applicable alongside graph optimizations and transforms. ONNX Runtime training can accelerate the model training time on multi-node NVIDIA GPUs for transformer models with a one-line addition for existing PyTorch training scripts. Support for a variety of frameworks, operating systems and hardware platforms. Built-in optimizations that deliver up to 17X faster inferencing and up to 1.4X faster training.
