Search Results for "mac framework"
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15 projects for "mac framework" with 2 filters applied:
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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.... -
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GoogleTest
Google Testing and Mocking Framework
GoogleTest is Google's C++ mocking and test framework. It's used by many internal projects at Google, as well as a number of notable projects such as The Chromium projects, the OpenCV computer vision library, and the LLVM compiler. This GoogleTest project is actually a union of what used to be two separate projects: the old GoogleTest and GoogleMock, an extension of GoogleTest for writing and using C++ mock classes. Since they were so closely related, they were merged to create an even... -
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Open-AutoGLM
An open phone agent model & framework
Open-AutoGLM is an open-source framework and model designed to empower autonomous mobile intelligent assistants by enabling AI agents to understand and interact with phone screens in a multimodal manner, blending vision and language capability to control real devices. It aims to create an “AI phone agent” that can perceive on-screen content, reason about user goals, and execute sequences of taps, swipes, and text input via automated device control interfaces like ADB, enabling hands-off... -
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Golang Telegram Bot
Telegram Bot API Go framework
Telegram Bot API Go framework. -
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LiteRT-LM
LiteRT-LM is Google's production-ready inference framework
LiteRT-LM is Google’s open-source inference framework for deploying large language models on edge devices. It is built for production-oriented local LLM execution across Android, iOS, desktop, web, embedded, and IoT environments. The framework focuses on performance, hardware acceleration, and efficient model serving close to the user instead of relying only on remote cloud inference. It supports CPU execution across major platforms and adds GPU or NPU acceleration where available. LiteRT-LM... -
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ncnn
High-performance neural network inference framework for mobile
ncnn is a high-performance neural network inference computing framework designed specifically for mobile platforms. It brings artificial intelligence right at your fingertips with no third-party dependencies, and speeds faster than all other known open source frameworks for mobile phone cpu. ncnn allows developers to easily deploy deep learning algorithm models to the mobile platform and create intelligent APPs. It is cross-platform and supports most commonly used CNN networks, including... -
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nndeploy
An Easy-to-Use and High-Performance AI Deployment Framework
nndeploy is an open-source framework designed to simplify the deployment of artificial intelligence models across multiple hardware platforms and devices. The framework focuses on making it easier to transform trained AI models into production-ready applications that can run efficiently on desktops, mobile devices, servers, and edge computing hardware. Developers can use visual workflows to design and configure AI processing pipelines by connecting modular nodes that represent different... -
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Phone Harness
Let your agent control your phone
Phone Harness is a lightweight system that lets AI coding agents interact directly with a real iPhone through macOS iPhone Mirroring. It requires no jailbreak, Xcode project, WebDriverAgent, or custom software installed on the phone. Screenshots of the mirrored window provide visual input, while Apple's Vision framework extracts visible text and tap-ready coordinates. macOS CGEvents supply taps, long presses, drags, scrolling, keyboard input, and iPhone Mirroring shortcuts. After performing... -
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AiToEarn
Let's use AI to Earn
AiToEarn is an open-source, AI-powered platform designed to help creators, brands, and businesses automate the entire content marketing lifecycle, from ideation and production to distribution and monetization. It aims to be a unified solution where users can generate content, tailor it for multiple platforms, and publish it across social networks with minimal manual effort. The project supports matrix publishing to major global platforms like TikTok, YouTube, Instagram, Facebook, Pinterest,... -
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AskUI Vision Agent
Enable AI to control your desktop, mobile and HMI devices
AskUI’s Vision Agent is an automation framework that allows you—and AI agents—to control real desktops, mobile devices, and HMI systems by perceiving the UI and performing actions like clicking, typing, scrolling, and drag-and-drop. It is designed for multi-platform compatibility and supports multiple AI models so you can tailor perception and decision-making to your workload. The repository presents a feature overview, sample media, and frequent release notes, which show ongoing... -
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LLMFarm
llama and other large language models on iOS and MacOS offline
LLMFarm is a framework designed to simplify the deployment, management, and utilization of large language models in local or self-hosted environments, focusing on accessibility and efficient resource usage. It enables users to run LLMs on personal hardware or private infrastructure, reducing dependency on external APIs and improving data privacy. The system typically provides a user-friendly interface for loading models, configuring inference parameters, and interacting with them through... -
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pipeless
A computer vision framework to create and deploy apps in minutes
Pipeless is an open-source computer vision framework to create and deploy applications without the complexity of building and maintaining multimedia pipelines. It ships everything you need to create and deploy efficient computer vision applications that work in real-time in just minutes. Pipeless is inspired by modern serverless technologies. It provides the development experience of serverless frameworks applied to computer vision. You provide some functions that are executed for new... -
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KotlinDL
High-level Deep Learning Framework written in Kotlin
KotlinDL is a high-level Deep Learning API written in Kotlin and inspired by Keras. Under the hood, it uses TensorFlow Java API and ONNX Runtime API for Java. KotlinDL offers simple APIs for training deep learning models from scratch, importing existing Keras and ONNX models for inference, and leveraging transfer learning for tailoring existing pre-trained models to your tasks. This project aims to make Deep Learning easier for JVM and Android developers and simplify deploying deep learning... -
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libcrn is document image processing library written in C++11 for Linux, Windows, Mac OsX and Google Android. It is a toolbox that allows to create easily software such as OCRs and layout analysis tools.
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Fast Artificial Neural Network Library is a free open source neural network library, which implements multilayer artificial neural networks in C with support for both fully connected and sparsely connected networks. Cross-platform execution in both fixed and floating point are supported. It includes a framework for easy handling of training data sets. It is easy to use, versatile, well documented, and fast. Bindings to more than 15 programming languages are available. An easy to read...
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