Search Results for "data vision" - Page 3
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Showing 170 open source projects for "data vision"
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Find Hidden Risks in Windows Task SchedulerWindows Task Scheduler might be hiding critical failures. Download the free JAMS diagnostic tool to uncover problems before they impact production—get a color-coded risk report with clear remediation steps in minutes.
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AI-generated apps that pass security reviewRetool lets you generate dashboards, admin panels, and workflows directly on your data. Type something like “Build me a revenue dashboard on my Stripe data” and get a working app with security, permissions, and compliance built in from day one. Whether on our cloud or self-hosted, create the internal software your team needs without compromising enterprise standards or control.
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NVIDIA NeMo Framework
Scalable generative AI framework built for researchers and developers
...The framework builds on PyTorch Lightning–style modular abstractions, so training scripts are composed from reusable components for data loading, models, optimizers, and schedulers, which simplifies experimentation and adaptation. NeMo is designed to scale: with tools like NeMo-Run, users can orchestrate large-scale experiments across thousands of GPUs. -
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Seamless Communication
Foundational Models for State-of-the-Art Speech and Text Translation
Seamless Communication is a research project focused on building more integrated, low-latency multimodal communication between humans and AI agents. The motivation is to move beyond “text in, text out” and enable direct, live, multi-turn exchange involving language, gesture, gaze, vision, and modality switching without user friction. The system architecture includes a real-time multimodal signal pipeline for audio, video, and sensor data, a dialog manager that can decide when to act (speak, gesture, point) or query, and a cross-modal reasoning layer that fuses perception with semantic context. The research prototype includes components for visual grounding (understanding when a user references something in view), gesture recognition and synthesis, and turn-taking mechanisms that mirror human conversational timing. ... -
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pyrebel
Abstract representation of data for machine vision
A pure python library that implements abstraction of data. -
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UoMqVXL
Qt based GUI classes for the VXL Computer Vision Libraries
Qt based GUI classes for VXL from the University of Manchester. Includes libraries to display VXL images and graphics, including shape model manipulation. Also includes tools to display images and points, and to annotate images with points. -
Atera all-in-one platform IT management software with AI agentsAtera’s AI agents don’t just assist, they act. From detection to resolution, they handle incidents and requests instantly, taking your IT management from automated to autonomous.
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magiconic
Magiconic provides generative models conducting both visual & language
The Magiconic project provides generative models conducting both visual data and language data like vision language model. -
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Armadillo
fast C++ library for linear algebra & scientific computing
* Fast C++ library for linear algebra (matrix maths) and scientific computing * Easy to use functions and syntax, deliberately similar to Matlab / Octave * Uses template meta-programming techniques to increase efficiency * Provides user-friendly wrappers for OpenBLAS, Intel MKL, LAPACK, ATLAS, ARPACK, SuperLU and FFTW libraries * Useful for machine learning, pattern recognition, signal processing, bioinformatics, statistics, finance, etc. * Downloads:... -
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Arnis Minecraft city generator download
Generate any location from the real world in Minecraft Java Edition
...Whether you're looking to replicate your hometown, explore urban environments, or simply build something unique and realistic, Arnis generates your vision. -
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Umbrel AMD64 usb installer image
Umbrel Img Image
USB img file of Umbrel OS formatted from umbrelos-amd64-usb-installer.iso umbrelOS A beautiful home server OS for self-hosting umbrel.com » At Umbrel, we believe that everyone should be able to enjoy the convenience and benefits of the cloud, without giving up ownership and control of their data. To achieve our vision, we're building a new kind of a home server OS. Instead of paying ransoms for storing your data on someone else's computer while they auction it off to advertisers — you can now easily spin up a server and self-host your data and services at home. Just like the cloud, but one that you own and control. -
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AWA-Core
Full application for factory, process engineer and Automation..
IT'S HERE-----FINALLY. AWA-Core 2026 is here with a totally new architecture. The core is now in Client/Server architecture and open to other applications (including yours). New interfaces for the server and client sides. Please, go to our youTube channel to see many tutorials about this new release. Don't waste your time trying things and clicking everywhere. Wait for our tutorials, install AWA-Core on a single PC or in a complete C/S architecture (Servers provided) and run... -
Desktop and Mobile Device Management SoftwareDesktop Central is a unified endpoint management (UEM) solution that helps in managing servers, laptops, desktops, smartphones, and tablets from a central location.
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CIApp
CIApp is an innovative application designed to track and count reps
...Customizable Workouts: Tailors to individual preferences by supporting a variety of exercise types. Suitable for both individual users and fitness coaches monitoring clients. Data Insights and Progress Tracking: Tracks historical data to monitor improvements -
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iceWing is a graphical plugin shell optimized for, but not limit to, image processing and vision system development. Predefined or self-written plugins operate hierarchically on data provided by other plugins and can also generate new data-streams. An important predefined plugin can read images and videos from disk in various formats, from grabber-hardware, e.g. V4L2-devices or FireWire, and also from external, network wide processes.
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Engine_3D
A real-time 3D engine for DOS-talgics (see GLOBE_3D for new stuff !)
Engine_3D is a real-time 3D engine project grabbed from my old data. The entire 3D rendering is pure software: no OpenGL or the like, no 3D graphics card acceleration! And: Engine_3D is completely programmed in Ada. Some parts of the 3D engine, like the animated bump mapping, are still waiting to be ported to my newer 3D project, GLOBE_3D !... DOS and Linux versions available. Remarks for the DOS version: It is also a funny example of a game system almost fully in Ada,... -
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opticsbenchui
Software for the automation of optics lab experiments
Data are saved in a hierachical way, adapted to scan profiles (HDF5 file format). The graphical user interface is based on open source Qt. -
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FastAI.jl
Repository of best practices for deep learning in Julia
FastAI.jl is a Julia library for training state-of-the-art deep learning models. From loading datasets and creating data preprocessing pipelines to training, FastAI.jl takes the boilerplate out of deep learning projects. It equips you with reusable components for every part of your project while remaining customizable at every layer. FastAI.jl comes with support for common computer vision and tabular data learning tasks, with more to come. -
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OpenEagle
Synthetic Vision/Sectional Maps for experimental aircraft.
OpenEagle provides interfacing to Flightgear to create a synthetic view of the flight using a Garmin G5 EFIS, and other instruments to display the flight at 10hz. The system also includes tools to make and use browser based moving maps from the FAA sectional "tif" files free to download. OpenEagle replaces NAV, and FIX databases in Flightgear with current FAA data. FAA Special rules airspace such as Class B,C, and D, and MOA's et al are displayed in the synthetic view using translucent... -
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DataGym.ai
Open source annotation and labeling tool for image and video assets
DATAGYM enables data scientists and machine learning experts to label images up to 10x faster. AI-assisted annotation tools reduce manual labeling effort, give you more time to finetune ML models and speed up your go to market of new products. Accelerate your computer vision projects by cutting down data preparation time up to 50%. A machine learning model is only as good as its training data. -
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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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T81 558
Applications of Deep Neural Networks
...Application of these architectures to computer vision, time series, security, natural language processing (NLP), and data generation will be covered. High-Performance Computing (HPC) aspects will demonstrate how deep learning can be leveraged both on graphical processing units (GPUs), as well as grids. -
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PIFuHD
High-Resolution 3D Human Digitization from A Single Image
PIFuHD (Pixel-Aligned Implicit Function for 3D human reconstruction at high resolution) is a method and codebase to reconstruct high-fidelity 3D human meshes from a single image. It extends prior PIFu work by increasing resolution and detail, enabling fine geometry in cloth folds, hair, and subtle surface features. The method operates by learning an implicit occupancy / surface function conditioned on the image and camera projection; at inference time it queries dense points to reconstruct a... -
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FFCV
Fast Forward Computer Vision (and other ML workloads!)
ffcv is a drop-in data loading system that dramatically increases data throughput in model training. From gridding to benchmarking to fast research iteration, there are many reasons to want faster model training. Below we present premade codebases for training on ImageNet and CIFAR, including both (a) extensible codebases and (b) numerous premade training configurations. -
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Self-learning-Computer-Science
Resources to learn computer science in your spare time
Self-learning Computer Science is a curated, open-source guide repository designed to help learners independently study computer science topics using high-quality university-level resources. The author (an undergraduate CS student) assembled links to courses from institutions like MIT, UC Berkeley, Stanford, etc., covering mathematics, programming, data structures/algorithms, computer architecture, machine learning, software engineering and more. It’s aimed at learners who find traditional... -
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giv, The G(reat|tk|NU) Image Viewer, is a 8-bit to 32-bit and floating point image and vector viewer for gtk+. It is designed especially for scientific vision and computational geometry and has support for drawing vector graphics on top of an image.
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ml-surveys
Survey papers summarizing advances in deep learning, NLP, CV, graphs
...It is particularly useful for researchers, data scientists, or engineers who want conceptual clarity about where a field stands, what problems remain, and what techniques are most established. -
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AirSim
A simulator for drones, cars and more, built on Unreal Engine
...It is developed as an Unreal plugin that can simply be dropped into any Unreal environment. AirSim's development is oriented towards the goal of creating a platform for AI research to experiment with deep learning, computer vision and reinforcement learning algorithms for autonomous vehicles. For this purpose, AirSim also exposes APIs to retrieve data and control vehicles in a platform independent way. AirSim is fully enabled for multiple vehicles. This capability allows you to create multiple vehicles easily and use APIs to control them. -
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MAE (Masked Autoencoders)
PyTorch implementation of MAE
MAE (Masked Autoencoders) is a self-supervised learning framework for visual representation learning using masked image modeling. It trains a Vision Transformer (ViT) by randomly masking a high percentage of image patches (typically 75%) and reconstructing the missing content from the remaining visible patches. This forces the model to learn semantic structure and global context without supervision. The encoder processes only the visible patches, while a lightweight decoder reconstructs the...
