Search Results for "vision"
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Showing 42 open source projects for "vision"
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1
Kornia
Open Source Differentiable Computer Vision Library
...With Kornia we fill the gap between classical and deep computer vision that implements standard and advanced vision algorithms for AI. Our libraries and initiatives are always according to the community needs. -
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Albumentations
Fast image augmentation library and an easy-to-use wrapper
Albumentations is a computer vision tool that boosts the performance of deep convolutional neural networks. Albumentations is a Python library for fast and flexible image augmentations. Albumentations efficiently implements a rich variety of image transform operations that are optimized for performance, and does so while providing a concise, yet powerful image augmentation interface for different computer vision tasks, including object classification, segmentation, and detection. ... -
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MIVisionX
Set of comprehensive computer vision & machine intelligence libraries
MIVisionX toolkit is a set of comprehensive computer vision and machine intelligence libraries, utilities, and applications bundled into a single toolkit. AMD MIVisionX delivers highly optimized open-source implementation of the Khronos OpenVX™ and OpenVX™ Extensions along with Convolution Neural Net Model Compiler & Optimizer supporting ONNX, and Khronos NNEF™ exchange formats. The toolkit allows for rapid prototyping and deployment of optimized computer vision and machine learning inference workloads on a wide range of computer hardware, including small embedded x86 CPUs, APUs, discrete GPUs, and heterogeneous servers. ... -
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ArrayFire
ArrayFire, a general purpose GPU library
ArrayFire is a general-purpose tensor library that simplifies the process of software development for the parallel architectures found in CPUs, GPUs, and other hardware acceleration devices. The library serves users in every technical computing market. Data structures in ArrayFire are smartly managed to avoid costly memory transfers and to take advantage of each performance feature provided by the underlying hardware. The community of ArrayFire developers invites you to build with us if... -
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Flax
Flax is a neural network library for JAX
...Flax emphasizes composability: optimizers, training loops, and checkpointing are provided as examples or utilities rather than monolithic frameworks, encouraging research-friendly customization. The library is widely used in vision, language, and reinforcement learning, often serving as a thin layer atop NumPy-like JAX primitives. Tutorials and examples show patterns for multi-host training, mixed precision, and advanced input pipelines that scale from laptops to TPUs. -
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MuJoCo Playground
An open source library for GPU-accelerated robot learning
...The project includes classic control benchmarks from dm_control, advanced quadruped and bipedal locomotion systems, and dexterous as well as non-prehensile manipulation setups. It also offers optional vision-based training capabilities through integration with Madrona-MJX, allowing researchers to train policies directly from image input on GPUs. MuJoCo Playground supports both the MJX JAX implementation and the Warp physics engine, enabling flexible use across research pipelines. The environments are designed for fast training, compatibility with reinforcement learning libraries, and real-time trajectory visualization using rscope. -
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React ChatBotify
A modern React library for creating flexible and extensible chatbots
...Whether you're aiming to create a simple FAQ bot or a sophisticated conversational interface integrated with Large Language Models (LLMs), React ChatBotify provides the tools and flexibility you need to bring your vision to life. -
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CO3D (Common Objects in 3D)
Tooling for the Common Objects In 3D dataset
CO3Dv2 (Common Objects in 3D, version 2) is a large-scale 3D computer vision dataset and toolkit from Facebook Research designed for training and evaluating category-level 3D reconstruction methods using real-world data. It builds upon the original CO3Dv1 dataset, expanding both scale and quality—featuring 2× more sequences and 4× more frames, with improved image fidelity, more accurate segmentation masks, and enhanced annotations for object-centric 3D reconstruction. -
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Covalent
Teradata UI Platform built on Angular Material
Reusable tested tools to build robust Angular Material & Angular applications. Vision: To build an atomic, reusable component platform for Teradata to consume, while collaborating in an open-source model. Covalent is a reusable UI platform from Teradata for building web applications with common standards and tooling. It is based on Angular and Material Design. Visualize your data easily. ECharts is an extensive "tried and true" charting library brought to Angular as Covalent Charts. td-chart-x-axis and td-chart-y-axis elements generate an axis inside a td-chart. ... -
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PrimeReact
The Most Complete React UI Component Library
Elevate your web applications with PrimeReact's comprehensive suite of customizable, feature-rich UI components. With PrimeReact, turning your development vision into reality has never been easier. The ultimate set of UI Components to assist you with 80+ impressive React Components. Choose from a variety of pre-built themes or implement your design systems with the CSS library of your choice like TailwindCSS. Connect with the other open-source community members, collaborate, and have a voice in the project roadmap. ... -
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Images.jl
An image library for Julia
...It is not yet as complete as some toolkits for other programming languages, but it has many useful algorithms. It is focused on clean architecture and is designed to unify "machine vision" and "biomedical 3d image processing" communities. -
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UCO3D
Uncommon Objects in 3D dataset
uCO3D is a large-scale 3D vision dataset and toolkit centered on turn-table videos of everyday objects drawn from the LVIS taxonomy. It provides about 170,000 full videos per object instance rather than still frames, along with per-video annotations including object masks, calibrated camera poses, and multiple flavors of point clouds. Each sequence also ships with a precomputed 3D Gaussian Splat reconstruction, enabling fast, differentiable rendering workflows and modern implicit/point-based modeling experiments. ... -
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CoreNet
CoreNet: A library for training deep neural networks
...Its distributed runtime manages synchronization, load balancing, and mixed-precision computation to maximize throughput while minimizing communication bottlenecks. CoreNet integrates tightly with Apple’s proprietary ML stack and hardware, serving as the foundation for research in computer vision, language models, and multimodal systems within Apple AI. The framework includes monitoring tools, fault tolerance mechanisms, and efficient checkpointing for massive training runs. -
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Multimodal
TorchMultimodal is a PyTorch library
This project, also known as TorchMultimodal, is a PyTorch library for building, training, and experimenting with multimodal, multi-task models at scale. 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. ... -
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Theseus
A library for differentiable nonlinear optimization
Theseus is a library for differentiable nonlinear optimization that lets you embed solvers like Gauss-Newton or Levenberg–Marquardt inside PyTorch models. Problems are expressed as factor graphs with variables on manifolds (e.g., SE(3), SO(3)), so classical robotics and vision tasks—bundle adjustment, pose graph optimization, hand–eye calibration—can be written succinctly and solved efficiently. Because solves are differentiable, you can backpropagate through optimization to learn cost weights, feature extractors, or initialization networks end-to-end. The implementation supports batched optimization on GPU, robust losses, damping strategies, and custom factors, making it practical for real-time systems. ... -
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fvcore
Collection of common code shared among different research projects
fvcore is a lightweight utility library that factors out common performance-minded components used across Facebook/Meta computer-vision codebases. It provides numerics and loss layers (e.g., focal loss, smooth-L1, IoU/GIoU) implemented for speed and clarity, along with initialization helpers and normalization layers for building PyTorch models. Its common modules include timers, logging, checkpoints, registry patterns, and configuration helpers that reduce boilerplate in research code. ... -
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Delphi : VRCalc++ OOSL (Script) and more
Delphi : VRCalc++ OOSL & + (Paged List, TextEditor, VRAstroVision ...)
Vincent Radio {Adrix.NT} Sources Library & Applications : Delphi C++ Java VRCalc++ C# VRCalc++ Object Oriented Scripting Language - Engine Source Pascal Code - Delphi Packages Build Prjs - VRCalc++ Scripted System Std RT Library - Guides & Docs (CHM, PDF, DOCX) - VCL & FMX (FireMonkey) Support - Script Test Code (Lang RTL VCL FMX) - Visual Stage Project : VCL & FMX Paged Lists & Iterators : Delphi C++ Java C# Multi-Dim Arrays & Direct Graph Classes : Delphi C++ Java VRCalc++ C# Delphi Drag&Drop Applications - VRCalc++ Script Executors: Terminal, VCL, FMX - VRMultiEdit - VRLazyCodeEditor - VR Astro Vision (Astrology) - Paged List Test - VRMosaic : Delphi C++Builder Java C# +with auto resolver - VR Free Chess 2D - VRBlocks - VRGraphStage - VR TTT OX + icons & bitmaps + VCL VisualStyles + Build Projects + instructions to build projects to build projects - Delphi : RAD Studio - C++ : Dev-C++ - java : NetBeans - C# : MS/VS adrixnt@hotmail.it -
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HARFANG 3D engine
HARFANG 3D source code public repository
...Its software suite is tailored to developers, designers and engineers aiming to efficiently and seamlessly develop, implement & deploy 3D solutions (HMI, VR/AR, simulation, interactive 3D), regardless of development language or platform constraints. HARFANG Studio is the ideal 3D editor for creating real-time scenes & animations that match your design vision. It can manage the entire 3D graphics production workflow in a simple and optimized manner, without compromising the integration in other development environments. HARFANG Studio’s philosophy is in line with that of HARFANG 3D engine, a compliant, straightforward, fast & lightweight. Everything that runs in HARFANG Studio is compatible with our Framework and its supported coding languages. ... -
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iJEPA
Official codebase for I-JEPA
...This objective sidesteps generative pixel losses and avoids heavy negative sampling, producing features that transfer strongly with linear probes and minimal fine-tuning. The design scales naturally with Vision Transformer backbones and flexible masking strategies, and it trains stably at large batch sizes. i-JEPA’s predictions are made in embedding space, which is computationally efficient and better aligned with downstream discrimination tasks. The repository provides training recipes, data pipelines, and evaluation code that clarify which masking patterns and architectural choices matter most. -
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DeepMind Research
Implementations and code to accompany DeepMind publications
This repository collects reference implementations and illustrative code accompanying a wide range of DeepMind publications, making it easier for the research community to reproduce results, inspect algorithms, and build on prior work. The top level organizes many paper-specific directories across domains such as deep reinforcement learning, self-supervised vision, generative modeling, scientific ML, and program synthesis—for example BYOL, Perceiver/Perceiver IO, Enformer for genomics, MeshGraphNets for physics, RL Unplugged, Nowcasting for weather, and more. Each project folder typically includes its own README, scripts, and notebooks so you can run experiments or explore models in isolation, and many link to associated datasets or external environments like DeepMind Lab and StarCraft II. ... -
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ml-surveys
Survey papers summarizing advances in deep learning, NLP, CV, graphs
The ml-surveys repository is a broad, maintainable overview of survey papers across many subfields of machine learning — including deep learning, NLP, computer vision, graph ML, reinforcement learning, recommendation systems, embeddings, meta-learning, and more. Instead of diving into code or experiments, this repo gathers authoritative survey and review articles, summarizing the state-of-the-art, trends, challenges, and directions within each subdomain. For someone trying to get up to speed with a new ML subfield — say graph neural networks or meta-learning — ml-surveys offers a curated reading list of foundational and recent works, helping map the landscape quickly. ... -
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Darknet
Convolutional Neural Networks
...With GPU acceleration via CUDA and OpenCV integration, it achieves high performance in image recognition tasks. Its simplicity, combined with powerful capabilities, has made Darknet one of the most influential projects in the computer vision community. -
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Flux3D.jl
3D computer vision library in Julia
Flux3D.jl is a 3D vision library, written completely in Julia. This package utilizes Flux.jl and Zygote.jl as its building blocks for training 3D vision models and for supporting differentiation. This package also have support of CUDA GPU acceleration with CUDA.jl. -
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CameraVoyeur
Windows-oriented utility to log frames from a connected camera devices
...This makes it useful for developers who want to add camera capture to a Windows tool or who need a barebones sample to build surveillance, monitoring, or computer vision toys on top of. Its value is really in being a simple, readable reference rather than a big camera suite. -
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Nerfies
This is the code for Deformable Neural Radiance Fields
...A set of utilities manages dataset preparation, pose estimation, and checkpoints so researchers can reproduce results on their own footage. The work sits at the intersection of graphics and vision, showing how learned volumetric rendering can handle human motion without dense markers or studio rigs.
