Search Results for "odin source code" - Page 79
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Showing 16074 open source projects for "odin source code"
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TypeSpec
Language for defining cloud service APIs and shapes
TypeSpec is a language for defining cloud service APIs and shapes. TypeSpec is a highly extensible language with primitives that can describe API shapes common among REST, OpenAPI, gRPC, and other protocols. TypeSpec is excellent for generating many different API description formats, client and service codes, documentation, and many other assets. All this while keeping your TypeSpec definition as a single source of truth. Using TypeSpec, you can create reusable patterns for all aspects of an... -
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Sisk Framework
Sisk's request and response processor mainframe source code
...The entire Sisk ecosystem is open source, and all the libraries and technologies we use are also open source. Sisk is entirely distributed under the MIT License, which allows commercial development. You are the one who makes the project, Sisk gives you the tools. Because it is open source, the community (including you) can maintain, fix bugs, and improve Sisk over time. -
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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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CVPR 2025
Collection of CVPR 2025 papers and open source projects
CVPR 2025 curates accepted CVPR 2025 papers and pairs them with their corresponding code implementations when available, giving researchers and practitioners a fast way to move from reading to reproducing. It organizes entries by topic areas such as detection, segmentation, generative models, 3D vision, multi-modal learning, and efficiency, so you can navigate the year’s output efficiently. Each paper entry typically includes a title, author list, and links to the paper PDF and official or... -
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Mall Learning
Tutorial and sample-code repository
mall-learning is a tutorial and sample-code repository that explores an entire e-commerce system architecture from backend to frontend. The associated “mall” project (with tens of thousands of stars) is an open-source full-stack e-commerce platform built with Spring Boot, MyBatis, Elasticsearch, RabbitMQ, Redis, MongoDB, MySQL and containerized via Docker. The learning repository breaks down architecture, business modules (products, orders, marketing, members), deployment (Linux, Docker, Jenkins) and technical points in detail. ... -
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Thinc
A refreshing functional take on deep learning
Thinc is a lightweight deep learning library that offers an elegant, type-checked, functional-programming API for composing models, with support for layers defined in other frameworks such as PyTorch, TensorFlow and MXNet. You can use Thinc as an interface layer, a standalone toolkit or a flexible way to develop new models. Previous versions of Thinc have been running quietly in production in thousands of companies, via both spaCy and Prodigy. We wrote the new version to let users compose,... -
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Json.NET
A popular high-performance JSON framework for .NET
...Query JSON with an XPath-like syntax. 50% faster than DataContractJsonSerializer, and 250% faster than JavaScriptSerializer. Json.NET makes the simple easy and the complex possible. If you need it, Json.NET supports converting between XML and JSON. Json.NET is open source software and is completely free for commercial use. Json.NET supports Windows, MacOS, Linux, Mono, and Xamarin. Over 1 billion downloads and counting, Json.NET is the number one library on NuGet. Json.NET documentation is the first place to go for help. It includes over 100 code samples. Json.NET is open source under the MIT license and is free for commercial use. -
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Google Gen AI SDK
Google Gen AI Python SDK provides an interface for developers
Google Gen AI Python SDK is Google’s official Python library for integrating Google generative AI models into Python applications. It supports both the Gemini Developer API and Google’s enterprise-oriented generative AI platform APIs, giving developers one SDK for consumer-facing and cloud-based Gemini workflows. The library provides a client-based interface for generating text, working with multimodal inputs, managing chats, handling files, using tools, and accessing model capabilities from... -
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Qodo Cover
AI tool that generates tests to improve code coverage quickly
Qodo Cover is an open source developer tool designed to automate the creation of unit tests using generative AI, helping teams improve code coverage with minimal manual effort. It operates as a command-line interface and can also be integrated into continuous integration workflows, making it adaptable to different development environments. It analyzes an existing codebase, identifies gaps in test coverage, and generates new tests that target uncovered or weakly tested areas. ... -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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draw-a-ui
Draw wireframe sketches and generate HTML with AI vision models
draw-a-ui is an experimental open source application that converts hand-drawn interface wireframes into working HTML code using artificial intelligence. draw-a-ui combines the tldraw canvas drawing tool with a vision-capable language model to interpret user-created mockups and translate them into a single HTML layout styled with Tailwind CSS. When a user sketches a UI on the canvas, the application captures the current drawing as SVG, converts it into a PNG image, and sends that image to a vision model that generates the corresponding markup. ... -
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machine learning tutorials
machine learning tutorials (mainly in Python3)
machine-learning is a continuously updated repository documenting the author’s learning journey through data science and machine learning topics using practical tutorials and experiments. The project presents educational notebooks that combine mathematical explanations with code implementations using Python’s scientific computing ecosystem. Topics covered include classical machine learning algorithms, deep learning models, reinforcement learning, model deployment, and time-series analysis.... -
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Machine learning algorithms
Minimal and clean examples of machine learning algorithms
Machine learning algorithms is an open-source repository that provides minimal and clean implementations of machine learning algorithms written primarily in Python. The project focuses on demonstrating how fundamental machine learning methods work internally by implementing them from scratch rather than relying on high-level libraries. This approach allows learners to study the mathematical and algorithmic details behind widely used models in a transparent and readable way. -
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Transfer Learning Repo
Transfer learning / domain adaptation / domain generalization
Transfer Learning Repo is an open-source repository that compiles resources, code implementations, and academic references related to transfer learning and its related research areas. The project functions as a large knowledge hub that organizes papers, tutorials, datasets, and software implementations across topics such as domain adaptation, domain generalization, multi-task learning, and few-shot learning. -
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ChatJS
Production-ready AI chat. Start here and make it your own
ChatJS is a production-ready AI chat foundation for developers who want to launch customizable chat applications without rebuilding common infrastructure from scratch. The project presents itself as a starting point that already includes authentication, model access, streaming, and tool support so teams can focus on their own product-specific features. Its stack is centered on modern TypeScript web development, using technologies such as Next.js, AI SDK tooling, PostgreSQL, Redis, and... -
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SwissGL
SwissGL is a minimalistic wrapper on top of WebGL2 JS API
SwissGL is a compact JavaScript library that provides a streamlined abstraction layer over the WebGL2 API, designed to minimize boilerplate when building GPU-accelerated graphics, simulations, and procedural visualizations. Acting as a "Swiss Army knife" for WebGL2, it simplifies shader, texture, and framebuffer management into a single, expressive interface that enables developers to write complex GPU workflows in just a few lines of code. The library centers around one main function that... -
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DINOv2
PyTorch code and models for the DINOv2 self-supervised learning
DINOv2 is a self-supervised vision learning framework that produces strong, general-purpose image representations without using human labels. It builds on the DINO idea of student–teacher distillation and adapts it to modern Vision Transformer backbones with a carefully tuned recipe for data augmentation, optimization, and multi-crop training. The core promise is that a single pretrained backbone can transfer well to many downstream tasks—from linear probing on classification to retrieval,... -
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crystalline
A Language Server Protocol implementation for Crystal
Crystalline is an implementation of the Language Server Protocol written in and for the Crystal Language. It aims to provide limited language features (like go-to, autocompletion, syntax and semantic checking) and ease development with any compatible code editor. Crystalline is not as extensive in terms of features as other Language Servers but still provides very convenient tools. Code Diagnostics. Syntax and semantic checks on save. Limited Autocompletion. List (depending on the target)... -
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Opacus
Training PyTorch models with differential privacy
...Open source, modular API for differential privacy research. Everyone is welcome to contribute. ML practitioners will find this to be a gentle introduction to training a model with differential privacy as it requires minimal code changes. Differential Privacy researchers will find this easy to experiment and tinker with, allowing them to focus on what matters. -
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NoneBot
Asynchronous multi-platform robot framework written in Python
Use NB-CLI to quickly build your own robot. Plug-in development, modular management. Supports multiple platforms and multiple incident response methods. Asynchronous priority development to improve operational efficiency. Simple and clear dependency injection system, built-in dependency functions reduce user code. NoneBot2 is a modern, cross-platform, and extensible Python chatbot framework. It is based on Python's type annotations and asynchronous features, and can provide convenient and... -
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Karate
Test automation made simple
Karate is the only open-source tool to combine API test-automation, mocks, performance-testing and even UI automation into a single, unified framework. The BDD syntax popularized by Cucumber is language-neutral, and easy for even non-programmers. Assertions and HTML reports are built-in, and you can run tests in parallel for speed. There’s also a cross-platform stand-alone executable for teams not comfortable with Java. -
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Compose Kotlin UI
A modern UI framework for Kotlin that makes building performant
Fast reactive desktop UIs for Kotlin, based on Google's modern toolkit and brought to you by JetBrains. Compose for Desktop simplifies and accelerates UI development for desktop applications, and allows extensive UI code sharing between Android and desktop applications. Currently in alpha. Compose for Desktop provides a declarative and reactive approach to creating user interfaces with Kotlin. Combine composable functions to build your user interface, and enjoy full tooling support from your... -
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Signature Pad
HTML5 canvas based smooth signature drawing
...It's HTML5 canvas based and uses variable width Bézier curve interpolation based on Smoother Signatures post by Square. It works in all modern desktop and mobile browsers and doesn't depend on any external libraries. Demo works in desktop and mobile browsers. You can check out its source code for some tips on how to handle window resize and high DPI screens. You can also find more about the latter in HTML5 Rocks tutorial. This library is provided as UMD (Universal Module Definition) and ES6 module. When you modify width or height of a canvas, it will be automatically cleared by the browser. SignaturePad doesn't know about it by itself, so you can call signaturePad.clear() to make sure that signaturePad.isEmpty() returns correct value in this case. -
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Claude Ads
Comprehensive paid advertising audit & optimization skill
Claude Ads is an AI-powered auditing and optimization tool designed to analyze paid advertising campaigns across multiple platforms using Claude Code. It processes user-provided data such as exports or screenshots and evaluates campaigns using hundreds of predefined checks. The system generates structured reports, identifies inefficiencies, and suggests optimization strategies based on industry benchmarks. It supports platforms like Google Ads, Meta Ads, TikTok, LinkedIn, and more, offering... -
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my-tv-0
My TV·〇 TV video playback device can customize the TV source
my-tv-0 is an open-source television streaming application that allows users to play video content from customizable sources, offering a flexible alternative to traditional IPTV solutions. The software supports multiple configuration formats, enabling users to define their own channel lists and video streams using files such as M3U, JSON, or TXT. It is designed to run on Android-based devices, including TV boxes and smart TVs, providing a simple interface for browsing and switching between... -
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Grounded Docs
Open-Source Alternative to Context7, Nia, and Ref.Tools
...This makes it easier for AI systems to answer technical questions, generate code examples, or retrieve reference material without requiring developers to manually integrate documentation into prompts. The architecture follows the MCP specification, which allows AI assistants and agent frameworks to connect to external tools through standardized protocols.
