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A python wrapper to extract text from images on a mac system. Uses the vision framework from Apple.
Thermo RAW file parser that runs on Linux/Mac and all other platforms that support Mono
Unlock the fullest potential of your device
Python app to work with pictures and associated metadata from Apple Photos on macOS. Also includes a package to provide programmatic access to the Photos library, pictures, and metadata.
Context7 MCP Server -- Up-to-date code documentation for LLMs and AI code editors
MCP 资源精选， MCP指南，Claude MCP，MCP Servers, MCP Clients
天天基金网 Node.js API service, 东方财富, 基金api, 基金接口, 股票接口
Enable Apple Intelligence on Macs sold in Mainland China with SIP enabled, tested on MacOS 15.4.1+ and 26.1 beta
MCP server providing seamless access to Apple Developer Documentation with smart search and wildcard support
Cook up amazing multimodal AI applications effortlessly with MiniCPM-o
Cross-platform, customizable ML solutions for live and streaming media.
MiniCPM-V 4.5: A GPT-4o Level MLLM for Single Image, Multi Image and High-FPS Video Understanding on Your Phone
DeepFashion2 Dataset https://arxiv.org/pdf/1901.07973.pdf
An easy way to uninstall Microsoft AutoUpdate on macOS.
CLI upload tool for tmp.link with resumable uploads, chunked transfers, and GUI interface.
Open Images is a dataset of ~9 million images that have been annotated with image-level labels and bounding boxes spanning thousands of classes.
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🐙 Guides, papers, lessons, notebooks and resources for prompt engineering, context engineering, RAG, and AI Agents.
This repository contains the official implementation of "FastVLM: Efficient Vision Encoding for Vision Language Models" - CVPR 2025
LLM.swift is a simple and readable library that allows you to interact with large language models locally with ease for macOS, iOS, watchOS, tvOS, and visionOS.
Various dictionaries compatible with the Dictionary.app in Mac OS X.
Custom Apple Dictionary support dark mode and offline pronunciation
A tool for converting dictionary files aka glossaries. Mainly to help use our offline glossaries in any Open Source dictionary we like on any operating system / device.