Search Results for "visual-mingw" - Page 8
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Showing 559 open source projects for "visual-mingw"
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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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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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HyperTools
A Python toolbox for gaining geometric insights
...Support for lists of Numpy arrays, Pandas dataframes, text or (mixed) lists. Applying topic models and other text vectorization methods to text data. HyperTools is designed to facilitate dimensionality reduction-based visual explorations of high-dimensional data. The basic pipeline is to feed in a high-dimensional dataset (or a series of high-dimensional datasets) and, in a single function call, reduce the dimensionality of the dataset(s) and create a plot. -
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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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Material Theme
A theme for Sublime Text 3 by Mattia Astorino
This theme brings the Material Design visual language to your Sublime Text 3. If you have problems, first search for a similar issue and then report a new one. If you want to enable the white panels and inputs you can install the addon package through Package Control, search for "Material theme white panels". You have to disable it if you want to use the Lighter theme style. -
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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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FireRed-Image-Edit
General-purpose image editing model that delivers high-fidelity
...It is built on a flexible text-to-image foundation model that has been extended with training paradigms including pretraining, supervised fine-tuning, and reinforcement learning to imbue the system with strong instruction following and editing consistency. The model excels in maintaining visual and text stylistic fidelity, allowing users to preserve the original artistic qualities of an image while applying creative changes according to natural language instructions. In addition to editing single images, FireRed supports multi-image editing scenarios such as virtual try-on or batch transformations, making it suitable for both creative and practical workflows. -
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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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AI Data Science Team
An AI-powered data science team of agents
...It provides a modular agent framework where each agent focuses on a step in the typical data science pipeline — for example, loading data from CSV/Excel files, cleaning and wrangling messy datasets, engineering predictive features, building models with AutoML, connecting to SQL databases, and producing visual outputs — all driven by natural language or programmatic instructions. The project includes ready-to-use applications that showcase these agents in action, such as an exploratory data analysis copilot that generates reports, a pandas data analyst that combines wrangling and plotting, and SQL database agents that can query business databases and output results directly. -
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LangExtract
A Python library for extracting structured information
...It is designed to transform free-form text into reliable, schema-constrained data while maintaining traceability back to the source material. Each extracted entity is precisely grounded in its original context, allowing visual inspection and validation via automatically generated interactive HTML visualizations. LangExtract supports a wide range of models, including Google Gemini, OpenAI GPT, and local LLMs via Ollama, making it adaptable to different deployment environments and compliance needs. The system excels at handling long documents using optimized chunking, multi-pass extraction, and parallel processing to ensure both high recall and structured consistency. -
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Multimodal
TorchMultimodal is a PyTorch library
...The design emphasizes composability: you can mix and match encoder, fusion, and decoder components rather than starting from monolithic models. The repository also includes example scripts and datasets for common multimodal tasks (e.g. retrieval, visual question answering, grounding) so you can test and compare models end to end. Installation supports both CPU and CUDA, and the codebase is versioned, tested, and maintained. -
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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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PyTorch3D
PyTorch3D is FAIR's library of reusable components for deep learning
...The library provides fast GPU-accelerated implementations of rendering pipelines, transformations, rasterization, and lighting—making it possible to compute gradients through full 3D rendering processes. Researchers use it for tasks like shape generation, reconstruction, view synthesis, and visual reasoning. PyTorch3D also includes utilities for loading, transforming, and sampling 3D assets, so models can be trained end-to-end from 2D supervision or partial data. Its modular design allows easy extension—components like differentiable rasterizers, mesh blending, or signed distance field (SDF) modules can be swapped or combined to test new architectures quickly. -
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VGGT
[CVPR 2025 Best Paper Award] VGGT
VGGT is a transformer-based framework aimed at unifying classic visual geometry tasks—such as depth estimation, camera pose recovery, point tracking, and correspondence—under a single model. Rather than training separate networks per task, it shares an encoder and leverages geometric heads/decoders to infer structure and motion from images or short clips. The design emphasizes consistent geometric reasoning: outputs from one head (e.g., correspondences or tracks) reinforce others (e.g., pose or depth), making the system more robust to challenging viewpoints and textures. ... -
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Perf Book
The book "Performance Analysis and Tuning on Modern CPU"
This project is a practical guide to performance analysis and tuning on modern CPUs, bridging microarchitecture details with hands-on profiling. It explains how caches, TLBs, prefetchers, branch predictors, and out-of-order execution influence real program speed, then connects those concepts to concrete optimization strategies. Readers learn how to design trustworthy benchmarks, avoid measurement traps (warmup, turbo, frequency scaling), and interpret hardware performance counters. The book... -
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PyVista
3D plotting and mesh analysis through a streamlined interface
...PyVista is a helper module for the Visualization Toolkit (VTK) that takes a different approach on interfacing with VTK through NumPy and direct array access. This package provides a Pythonic, well-documented interface exposing VTK’s powerful visualization backend to facilitate rapid prototyping, analysis, and visual integration of spatially referenced datasets. This module can be used for scientific plotting for presentations and research papers as well as a supporting module for other mesh-dependent Python modules. Easily integrate with NumPy and create a variety of geometries and plot them. You could use any geometry to create your glyphs, or even plot the points directly. ... -
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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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hCaptcha Challenger
Gracefully face hCaptcha challenge with multimodal llms
hCaptcha Challenger is an open-source automation framework designed to solve hCaptcha verification challenges using computer vision models and multimodal reasoning techniques. The project integrates machine learning models capable of analyzing visual captcha tasks and identifying the correct responses required to pass the verification process. Instead of relying on third-party captcha-solving services or browser scripts, the system operates independently by using pretrained neural networks that can classify images, detect objects, and interpret spatial relationships. The framework includes support for multiple types of captcha challenges such as object selection, drag-and-drop puzzles, and image labeling tasks. ... -
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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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AI-Codereview-Gitlab
GitLab automatic code review tool based on large models
AI-Codereview-Gitlab is an open-source automation tool that integrates large language models into the GitLab development workflow to perform automated code reviews. The system monitors GitLab repositories and analyzes commits or merge requests using AI models to identify potential issues, coding mistakes, and quality improvements before the code is merged. By leveraging multiple large language model providers—including OpenAI, DeepSeek, ZhipuAI, or local models through Ollama—the platform... -
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Luigi
Python module that helps you build complex pipelines of batch jobs
Luigi is a Python (3.6, 3.7, 3.8, 3.9 tested) package that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization, handling failures, command line integration, and much more. The purpose of Luigi is to address all the plumbing typically associated with long-running batch processes. You want to chain many tasks, automate them, and failures will happen. These tasks can be anything, but are typically long running things like Hadoop... -
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HunyuanOCR
OCR expert VLM powered by Hunyuan's native multimodal architecture
HunyuanOCR is an open-source, end-to-end OCR (optical character recognition) Vision-Language Model (VLM) developed by Tencent‑Hunyuan. It’s designed to unify the entire OCR pipeline, detection, recognition, layout parsing, information extraction, translation, and even subtitle or structured output generation, into a single model inference instead of a cascade of separate tools. Despite being fairly lightweight (about 1 billion parameters), it delivers state-of-the-art performance across a... -
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InternVL
A Pioneering Open-Source Alternative to GPT-4o
InternVL is a large-scale multimodal foundation model designed to integrate computer vision and language understanding within a unified architecture. The project focuses on scaling vision models and aligning them with large language models so that they can perform tasks involving both visual and textual information. InternVL is trained on massive collections of image-text data, enabling it to learn representations that capture both visual patterns and semantic meaning. The model supports a wide variety of tasks, including visual perception, image classification, and cross-modal retrieval between images and text. It can also be connected to language models to enable conversational interfaces that understand images, videos, and other visual content. ... -
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FreeCAD
a parametric 3D CAD modeler
This is an official mirror of FreeCAD. Code and release files are primarily hosted on https://github.com/FreeCAD/FreeCAD and mirrored here. FreeCAD is a general purpose feature-based, parametric 3D modeler for CAD, MCAD, CAx, CAE and PLM, aimed directly at mechanical engineering and product design but also fits a wider range of uses in engineering, such as architecture or other engineering specialties. It is 100% Open Source and extremely modular, allowing for very advanced extension and... -
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BioSig is a software library for processing of biomedical signals (EEG, ECG, etc.) with Matlab, Octave, C/C++ and Python. About 50 different data formats are supported.
