Showing 373 open source projects for "visual-cfd"

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  • 1
    Qwen3-VL-Embedding

    Qwen3-VL-Embedding

    Multimodal embedding and reranking models built on Qwen3-VL

    ...The reranking model then precisely scores relevance between a given query and candidate documents, enhancing retrieval accuracy in complex multimodal tasks. Together, they support advanced information retrieval workflows such as image-text search, visual question answering (VQA), and video-text matching, while providing out-of-the-box support for more than 30 languages.
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  • 2
    MiniMind-V

    MiniMind-V

    "Big Model" trains a visual multimodal VLM with 26M parameters

    MiniMind-V is an experimental open-source project that aims to train a very small multimodal vision–language model (VLM) from scratch with extremely low compute and cost, making research and experimentation accessible to more people. The repository showcases training workflows and code designed to produce a 26-million parameter model—including both image and text capabilities—using minimal resources in very little time, reflecting a trend toward democratizing AI research. MiniMind-V combines...
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  • 3
    Awesome-MCP-ZH

    Awesome-MCP-ZH

    Claude MCP, MCP Servers, MCP Clients

    Awesome-MCP-ZH is a curated, Chinese-language “awesome list” that maps the Model Context Protocol ecosystem for newcomers and practitioners. It organizes learning resources, how-tos, and explainers alongside living catalogs of MCP servers, clients, and tooling so users can get productive quickly. The curation emphasizes beginner-friendly on-ramps, including clients that bundle runtimes and one-click setups, as well as advanced references for power users. Regular updates and community stars...
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  • 4
    PaddleX

    PaddleX

    PaddlePaddle End-to-End Development Toolkit

    PaddleX is a deep learning full-process development tool based on the core framework, development kit, and tool components of Paddle. It has three characteristics opening up the whole process, integrating industrial practice, and being easy to use and integrate. Image classification and labeling is the most basic and simplest labeling task. Users only need to put pictures belonging to the same category in the same folder. When the model is trained, we need to divide the training set, the...
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  • 5
    zvt

    zvt

    Modular quant framework

    ...Your world is built by core concepts inside you, so it’s you. zvt world is built by core concepts inside the market, so it’s zvt. The core concept of the system is visual, and the name of the interface corresponds to it one-to-one, so it is also uniform and extensible. You can write and run the strategy in your favorite ide, and then view its related targets, factor, signal and performance on the UI. Once you are familiar with the core concepts of the system, you can apply it to any target in the market.
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  • 6
    ClawPort

    ClawPort

    Open-source AI agent command center for Claude Code agent teams

    ClawPort is an open-source web-based dashboard designed to act as a centralized command center for managing and interacting with OpenClaw AI agent systems. It provides a visual interface that replaces fragmented terminal-based workflows, allowing users to monitor, control, and communicate with multiple agents from a single location. The platform is built to improve visibility into multi-agent environments, offering insights into agent activity, task execution, and system performance in real time. It supports direct interaction with agents through chat interfaces, enabling users to guide or override automated workflows when necessary. ...
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  • 7
    MolmoWeb

    MolmoWeb

    Open multimodal web agent built by Ai2

    ...Unlike traditional automation tools that rely on structured HTML parsing or predefined APIs, MolmoWeb operates directly from screenshots of web pages, interpreting visual content in the same way a human user would. This approach allows it to generalize across different websites without requiring site-specific integrations, making it highly adaptable to diverse web environments.
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  • 8
    Browserbase MCP Server

    Browserbase MCP Server

    Allow LLMs to control a browser with Browserbase and Stagehand

    Browserbase MCP Server is a server implementation of the Model Context Protocol (MCP) that enables large language models to interact with web browsers programmatically through cloud-based automation. The project provides a standardized interface for connecting AI systems to real-world web environments, allowing them to navigate pages, extract structured data, and perform user-like actions such as clicking, typing, and form submission. It leverages Browserbase infrastructure along with...
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  • 9
    Short Video Factory

    Short Video Factory

    AI tool for automatic batch short video creation and editing

    Short Video Factory is an open source desktop application designed to simplify the creation of short-form videos using AI-driven automation. It enables users to generate product marketing clips and general content videos by combining simple prompt-based input with pre-prepared media assets. Short Video Factory integrates multiple stages of video production, including script generation, voice synthesis, video editing, and subtitle effects, into a single streamlined workflow. By leveraging AI...
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  • 10
    AntV Infographic

    AntV Infographic

    Declarative engine for generating AI-powered infographic visuals

    ...It also includes a built-in editor that allows users to refine and adjust generated infographics interactively after creation. With a large library of predefined templates and themes, AntV Infographic helps users rapidly prototype and produce consistent visual content.
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  • 11
    Interactive Machine Learning Experiments

    Interactive Machine Learning Experiments

    Interactive Machine Learning experiments

    Interactive Machine Learning Experiments is a collection of interactive demonstrations that showcase how various machine learning models can be trained and used in real applications. The project combines Jupyter or Colab notebooks with browser-based visual demos that allow users to see trained models operating in real time. Many experiments involve tasks such as image classification, object detection, gesture recognition, and simple generative models. The models are typically trained in Python using TensorFlow and then exported for interactive demonstrations in a web environment using JavaScript and TensorFlow.js. ...
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  • 12
    Diffusion for World Modeling

    Diffusion for World Modeling

    Learning agent trained in a diffusion world model

    ...Instead of interacting directly with a real environment, the reinforcement learning agent learns within a generative model that produces frames representing the environment. This approach allows training to occur in a simulated world that captures detailed visual dynamics while reducing the need for costly interactions with real environments. The system has been applied to tasks such as Atari game simulations and demonstrations involving complex environments like first-person shooter games.
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  • 13
    ChatWiki

    ChatWiki

    ChatWiki WeChat official account's AI knowledge base workflow agent

    ChatWiki is an open-source AI knowledge base and workflow automation platform designed to help organizations build intelligent question-answering systems using large language models and retrieval-augmented generation techniques. The system enables companies to transform internal documents and data into searchable knowledge bases that can power AI assistants capable of answering domain-specific questions. It provides a complete pipeline for ingesting documents, preprocessing and segmenting...
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  • 14
    ticket

    ticket

    Fast, powerful, git-native ticket tracking in a single bash script

    ...It stores each ticket as a Markdown file with YAML frontmatter, making them human-readable and easy to version control alongside your code, while also allowing IDEs to jump straight to ticket definitions. The CLI provides common subcommands to create, list, edit, close, and manage dependencies between tickets, enabling clear hierarchical task structures and visual dependency trees. Its design is rooted in the Unix philosophy of simplicity, composability, and transparency, meaning it integrates well with other standard tools like grep, jq, and ripgrep when installed. Teams can use ticket to track bugs, features, chores, and epics with priority levels and tags, all by staying within the terminal and Git ecosystem.
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  • 15
    Step3-VL-10B

    Step3-VL-10B

    Multimodal model achieving SOTA performance

    Step3-VL-10B is an open-source multimodal foundation model developed by StepFun AI that pushes the boundaries of what compact models can achieve by combining visual and language understanding in a single architecture. Despite having only about 10 billion parameters, it delivers performance that rivals or even surpasses much larger models (10×–20× larger) on a wide range of multimodal benchmarks covering reasoning, perception, and complex tasks, positioning it as one of the most powerful models in its class. ...
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  • 16
    MetaCLIP

    MetaCLIP

    ICLR2024 Spotlight: curation/training code, metadata, distribution

    ...It includes utilities to fine-tune vision-language embeddings, compute prompt or adapter updates, and benchmark across transfer and retention metrics. MetaCLIP is especially suited for real-world settings where a model must continuously incorporate new visual categories or domains over time.
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  • 17
    ImageReward

    ImageReward

    [NeurIPS 2023] ImageReward: Learning and Evaluating Human Preferences

    ImageReward is the first general-purpose human preference reward model (RM) designed for evaluating text-to-image generation, introduced alongside the NeurIPS 2023 paper ImageReward: Learning and Evaluating Human Preferences for Text-to-Image Generation. Trained on 137k expert-annotated image pairs, ImageReward significantly outperforms existing scoring methods like CLIP, Aesthetic, and BLIP in capturing human visual preferences. It is provided as a Python package (image-reward) that enables quick scoring of generated images against textual prompts, with APIs for ranking, scoring, and filtering outputs. Beyond evaluation, ImageReward supports Reward Feedback Learning (ReFL), a method for directly fine-tuning diffusion models such as Stable Diffusion using human-preference feedback, leading to demonstrable improvements in image quality.
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  • 18
    diff2html

    diff2html

    Pretty diff to html javascript library (diff2html)

    Each diff provides a comprehensive visualization of the code changes, helping developers identify problems and better understand the changes. Each diff features a line-by-line and side-by-side preview of your changes. All the code changes are syntax highlighted using highlight.js, providing more readability. Similar lines are paired, allowing for easier change tracking. We work hard to make sure you can have your diffs in a simple and flexible way. The AI community building the future....
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  • 19
    Vearch

    Vearch

    A distributed system for embedding-based vector retrieval

    ...Vearch implements a high-performance, lockless real-time vector indexing subsystem that utilizes various optimization techniques to support millisecond vector update and retrieval. End-to-end one-click deployment. Through the module of the plugin, a complete default visual search system can be deployed just with one click. Otherwise, you can easily customize your own image, video, or text feature extraction algorithm plugin. This GIF provides a clear demonstration of the project vearch usage and its internal structure. The use of vearch is mainly divided into three steps. Firstly, create DB and Space, then import your data, and finally, you can search on your own dataset.
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  • 20
    GoCV

    GoCV

    Go package for computer vision using OpenCV 4 and beyond

    ...Our mission is to make the Go language a “first-class” client compatible with the latest developments in the OpenCV ecosystem. Computer Vision (CV) is the ability of computers to process visual information, and perform tasks normally associated with those performed by humans. CV software typically processes video images, then uses the data to extract information in order to do something useful. Since memory allocations for images in GoCV are done through C based code, the go garbage collector will not clean all resources associated with a Mat. ...
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  • 21
    Magnitude

    Magnitude

    Vision AI browser agent for automation, testing, and extraction

    Browser Agent by Magnitude is an open source, vision-first browser automation framework that enables users to control web interfaces using natural language instructions. It leverages visually grounded AI models to interpret and interact with web pages based on what is seen on the screen rather than relying solely on the DOM structure. This approach allows the agent to generalize better across complex and modern websites, making it more robust than traditional selector-based automation tools....
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  • 22
    LLaMA-Mesh

    LLaMA-Mesh

    Unifying 3D Mesh Generation with Language Models

    ...By serializing 3D geometry into text tokens, the approach allows existing transformer architectures to generate and interpret 3D models without requiring specialized visual tokenizers. The project includes a supervised fine-tuning dataset composed of interleaved text and mesh data, allowing the model to learn relationships between textual descriptions and 3D structures. As a result, the model can generate mesh models directly from text prompts, explain mesh structures in natural language, or output mixed text-and-mesh sequences. ...
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  • 23
    Easy-Vibe

    Easy-Vibe

    Tutorial on Product Prototype, AI Capability Integration

    Easy-Vibe is an open-source educational project designed to teach developers, product managers, and beginners how to build AI-powered applications using the emerging concept of “vibe coding,” a development approach that relies heavily on AI-assisted programming tools. The project provides a structured curriculum that guides learners from having no programming experience to building fully functional AI-integrated applications. Instead of focusing only on theoretical concepts, Easy-Vibe...
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  • 24
    Map-Anything

    Map-Anything

    MapAnything: Universal Feed-Forward Metric 3D Reconstruction

    Map-Anything is a universal, feed-forward transformer for metric 3D reconstruction that predicts a scene’s geometry and camera parameters directly from visual inputs. Instead of stitching together many task-specific models, it uses a single architecture that supports a wide range of 3D tasks—multi-image structure-from-motion, multi-view stereo, monocular metric depth, registration, depth completion, and more. The model flexibly accepts different input combinations (images, intrinsics, poses, sparse or dense depth) and produces a rich set of outputs including per-pixel 3D points, camera intrinsics, camera poses, ray directions, confidence maps, and validity masks. ...
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  • 25
    DotVVM

    DotVVM

    Open source MVVM framework for Web Apps

    ...Just load data from the database and use data-binding to display them. DotVVM needs less than 100 kB of JavaScript code. It's smaller than other ASP.NET-based frameworks. DotVVM offers a free Visual Studio extension giving you all the comfort you are used to. DotVVM comes with ready-made components you can use in your HTML files. The state and user interactions are handled in view models - C# classes. The controls render simple HTML which can be styled easily. MVVM pattern and data-binding expressions are used to access the UI components.
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