Search Results for "visual 2 zone model"
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Showing 52 open source projects for "visual 2 zone model"
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DeepSeek-OCR 2
Visual Causal Flow
DeepSeek-OCR-2 is the second-generation optical character recognition system developed to improve document understanding by introducing a “visual causal flow” mechanism, enabling the encoder to reorder visual tokens in a way that better reflects semantic structure rather than strict raster scan order. It is designed to handle complex layouts and noisy documents by giving the model causal reasoning capabilities that mimic human visual scanning behavior, enhancing OCR performance on documents with rich spatial structure. ... -
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LTX-2.3
Official Python inference and LoRA trainer package
LTX-2.3 is an open-source multimodal artificial intelligence foundation model developed by Lightricks for generating synchronized video and audio from prompts or other inputs. Unlike most earlier video generation systems that only produced silent clips, LTX-2 combines video and audio generation in a unified architecture capable of producing coherent audiovisual scenes. The model uses a diffusion-transformer-based architecture designed to generate high-fidelity visual frames while simultaneously producing corresponding audio elements such as speech, music, ambient sound, or effects. ... -
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InternLM-XComposer-2.5
InternLM-XComposer2.5-OmniLive: A Comprehensive Multimodal System
InternLM-XComposer is an open-source multimodal AI system designed to generate long-form content that combines text with visual elements such as images and diagrams. The model is built on top of the InternLM language model architecture and extends its capabilities to handle multimodal inputs and outputs. Instead of producing only textual responses, the system can generate visually enriched documents such as illustrated articles, presentations, and educational materials. It incorporates... -
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VMZ (Video Model Zoo)
VMZ: Model Zoo for Video Modeling
The codebase was designed to help researchers and practitioners quickly reproduce FAIR’s results and leverage robust pre-trained backbones for downstream tasks. It also integrates Gradient Blending, an audio-visual modeling method that fuses modalities effectively (available in the Caffe2 implementation). Although VMZ is now archived and no longer actively maintained, it remains a valuable reference for understanding early large-scale video model training, transfer learning, and multimodal... -
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SAM 3
Code for running inference and finetuning with SAM 3 model
SAM 3 (Segment Anything Model 3) is a unified foundation model for promptable segmentation in both images and videos, capable of detecting, segmenting, and tracking objects. It accepts both text prompts (open-vocabulary concepts like “red car” or “goalkeeper in white”) and visual prompts (points, boxes, masks) and returns high-quality masks, boxes, and scores for the requested concepts. -
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Sa2VA
Official Repo For "Sa2VA: Marrying SAM2 with LLaVA
Sa2VA is a cutting-edge open-source multi-modal large language model (MLLM) developed by ByteDance that unifies dense segmentation, visual understanding, and language-based reasoning across both images and videos. It merges the segmentation power of a state-of-the-art video segmentation model (based on SAM‑2) with the vision-language reasoning capabilities of a strong LLM backbone (derived from models like InternVL2.5 / Qwen-VL series), yielding a system that can answer questions about visual content, perform referring segmentation, and maintain temporal consistency across frames in video. ... -
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Transformer Explainer
Learn How LLM Transformer Models Work with Interactive Visualization
Transformer Explainer is an interactive visualization tool created to help users understand how transformer-based language models operate internally. The platform runs a lightweight GPT-2 model directly in the user’s browser and allows users to experiment with text prompts while observing the model’s internal operations. Through visual diagrams and interactive interfaces, the tool reveals how tokens are processed through layers such as embeddings, attention mechanisms, and feed-forward networks. Users can observe how attention weights change as the model predicts the next token, offering insight into how transformer architectures capture relationships between words. ... -
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dtreeviz
Python library for decision tree visualization & model interpretation
A python library for decision tree visualization and model interpretation. Decision trees are the fundamental building block of gradient boosting machines and Random Forests(tm), probably the two most popular machine learning models for structured data. Visualizing decision trees is a tremendous aid when learning how these models work and when interpreting models. The visualizations are inspired by an educational animation by R2D3; A visual introduction to machine learning. ... -
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Learning Interpretability Tool
Interactively analyze ML models to understand their behavior
The Learning Interpretability Tool (LIT, formerly known as the Language Interpretability Tool) is a visual, interactive ML model-understanding tool that supports text, image, and tabular data. It can be run as a standalone server, or inside of notebook environments such as Colab, Jupyter, and Google Cloud Vertex AI notebooks. -
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MiniMax-01
Large-language-model & vision-language-model based on Linear Attention
MiniMax-01 is the official repository for two flagship models: MiniMax-Text-01, a long-context language model, and MiniMax-VL-01, a vision-language model built on top of it. MiniMax-Text-01 uses a hybrid attention architecture that blends Lightning Attention, standard softmax attention, and Mixture-of-Experts (MoE) routing to achieve both high throughput and long-context reasoning. It has 456 billion total parameters with 45.9 billion activated per token and is trained with advanced parallel... -
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Perception Models
State-of-the-art Image & Video CLIP, Multimodal Large Language Models
Perception Models is a state-of-the-art framework developed by Facebook Research for advanced image and video perception tasks. It introduces two primary components: the Perception Encoder (PE) for visual feature extraction and the Perception Language Model (PLM) for multimodal decoding and reasoning. The PE module is a family of vision encoders designed to excel in image and video understanding, surpassing models like SigLIP2, InternVideo2, and DINOv2 across multiple benchmarks. ... -
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Multimodal
TorchMultimodal is a PyTorch library
...The library provides modular building blocks such as encoders, fusion modules, loss functions, and transformations that support combining modalities (vision, text, audio, etc.) in unified architectures. It includes a collection of ready model classes—like ALBEF, CLIP, BLIP-2, COCA, FLAVA, MDETR, and Omnivore—that serve as reference implementations you can adopt or adapt. 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. ... -
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MLJAR Studio
Python package for AutoML on Tabular Data with Feature Engineering
We are working on new way for visual programming. We developed a desktop application called MLJAR Studio. It is a notebook-based development environment with interactive code recipes and a managed Python environment. All running locally on your machine. We are waiting for your feedback. The mljar-supervised is an Automated Machine Learning Python package that works with tabular data. It is designed to save time for a data scientist. It abstracts the common way to preprocess the data,... -
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git-tfs
A Git/TFS bridge, similar to git-svn
git-tfs is a two-way bridge between TFS (Team Foundation Server) and git, similar to git-svn. It fetches TFS commits into a git repository, and lets you push your updates back to TFS. git-tfs is a two-way bridge between TFS and git, similar to git-svn. If the build fails to build some GitTfs.Vs201x projects, just unload in Visual Studio all the projects you are not interested in to be able to build and use your own version. -
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DEVS-Suite Simulator
Component, CA, and CCA models; superdense time, DB repo, testing, etc.
...Version: 7.0 [Jan `23], 6.1 [Apr. `21], 6 [Sep. `20] , 5 [Jul. `19], 4 [Mar. `18], 3 [Apr. `15], 2.1 [Feb. `09], 2 [`03] See CoSMoSim: https://acims.asu.edu/software/cosmos : hierarchical visual modeling, database model repository, families of models, statecharts, partial-code generation for XML/DEVS-Suite model -
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Kisekae UltraKiss
Kisekae UltraKiss is a full featured integrated development environmen
UltraKiss is a computer program that implements the Kisekae Set system, KiSS, a Japanese graphics system originally developed to facilitate costume changes on virtual dolls. UltraKiss was developed to help artists build their KiSS sets. It is a full featured viewer for all KiSS dolls, games, and visual applications. It is also a complete graphical development environment for creating KiSS applications. It fully implements the FKiSS event driven programming language up to and including... -
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IEC 60870-5 101 Protocol Win C#
IEC 60870-5-101 Source code Library Stack - Windows c, c++, c# .net
v21,06.018 The complete implementation of IEC 101 protocol stack including File Transfer-Monitor, Balanced and Unbalanced mode, Directory Commands, Supports all type of Monitoring, command, parameter ASDUs. IEC 101 Windows SDK contains Win DLL (precompiled library), Static link lib, Demo IEC101 Server & Client programs, Visual Studio Demo console project files, Doxygen . We used Visual studio compiler to create the dll, sample test projects. FreyrSCADA offering 1) IEC101... -
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C/C++ Visio Like Diagramming Codes
Office Ribbon UI with Visio Like Diagramming And Drawing
1.Full C/C++ Source Codes. 2. Can be used within Web and C# 3. Office Ribbon UI. 4. Visio Like Diagramming 5. Visio Like Flowchart. 6. Visio Like Drawing. 7. Visio SVG Importing and Exporting. 8. C/C++ Source Codes are shipped. 9. Support All Visual Studios 10. All windows platform support. 11. HMI and SCADA support. 12. Model Design and Simulation. 13. -
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m2cgen
Transform ML models into a native code
m2cgen (Model 2 Code Generator) - is a lightweight library that provides an easy way to transpile trained statistical models into a native code (Python, C, Java, Go, JavaScript, Visual Basic, C#, PowerShell, R, PHP, Dart, Haskell, Ruby, F#, Rust, Elixir). Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies. -
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Microsoft Bot Framework SDK
Tool for building conversation applications
Bot Framework provides the most comprehensive experience for building conversation applications. With the Bot Framework SDK, developers can build bots that converse free-form or with guided interactions including using simple text or rich cards that contain text, images, and action buttons. Developers can model and build sophisticated conversation using their favorite programming languages including C#, JS, Python and Java or using Bot Framework Composer, an open-source, visual authoring... -
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PSRFM
A Prediction Smooth Method for Satellite Image Fusion
This PSRFM (Prediction Smooth Reflectance Fusion Model) software is a feature rich C++ program for blending Landsat or Sentinel-2 satellite images (higher spatial resolution but lower temporal frequency) with MODIS images ((lower spatial resolution but higher temporal frequency) to generate an exploitation-ready time series of synthetic images (higher spatial resolution and temporal frequency). -
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FID score for PyTorch
Compute FID scores with PyTorch
This is a port of the official implementation of Fréchet Inception Distance to PyTorch. FID is a measure of similarity between two datasets of images. It was shown to correlate well with human judgement of visual quality and is most often used to evaluate the quality of samples of Generative Adversarial Networks. FID is calculated by computing the Fréchet distance between two Gaussians fitted to feature representations of the Inception network. The weights and the model are exactly the same as in the official Tensorflow implementation, and were tested to give very similar results (e.g. .08 absolute error and 0.0009 relative error on LSUN, using ProGAN generated images). ... -
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Model United Nations Meeting Recorder
A fully-functioned meeting recorder.
A fully-functioned meeting recorder. -
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VB .NET PHYSX (PHYSICS) DX9 - Engine
.NET - VISUAL BASIC NVIDIA +ATI PHYSX SLIMDX DIRECTX 9 -ENGINE/WRAPPER
Visual Basic .Net , Nvidia Physx (PHYSICS - ATI INTEL ETC. COMPATIBLE) , DirectX 9 (using SlimDX) 3D ENGINE/HELPER/WRAPPER This project incorporates these technology into a simple Open Source Engine, allowing simple access to Nvidia PhysX library using DirectX 9 (VIA - SLIMDX) to render "Simulations/Games" ALL IN VB.NET -with- C# and other .NET language compatibility. Visuals now include .X model loading with Animations and Skeletons (shaders) Level loading and AUTOMATIC object (mesh)... -
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ciGen
ciGen is a short C++ code to generate cohesive interface elements.
Cohesive zone model (CZM) is a powerful method to study many cracking phenomena. Cohesive interface elements constitute a simple to implement yet valuable tool to implement CZM. This project provides a simple C++ code that reads a finite element mesh, modify it and generate cohesive interface elements where needed. It can read Gmsh (http://geuz.org/gmsh/) or ABAQUS input files and write the mesh to any format such as ABAQUS and jive (http://www.dynaflow.com/en_GB/jive.html). ...
