Search Results for "data capture framework" - Page 38
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Showing 2278 open source projects for "data capture framework"
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Input mask for iOS
User input masking library repo
Input masks restrict data input and allow you to guide users to enter correct values. Interface Builder struggles to support modules imported in a form of a dynamic framework. For instance, custom views annotated as IBDesignable, containing IBInspectable and IBOutlet fields aren't recognized properly from the drag'n'dropped framework. When you cut text, characters get deleted yet you won't be able to paste them somewhere as they aren't actually in your pasteboard. ... -
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Northwind Traders
Northwind Traders is a sample application built using ASP.NET Core
Northwind Traders is a sample business application created to demonstrate Clean Architecture in .NET Core. It separates domain rules, application logic, persistence, infrastructure, and presentation into distinct projects. The backend uses Entity Framework Core, while an Angular client provides the browser interface. MediatR organizes commands and queries, with FluentValidation handling request rules and AutoMapper translating data models. The solution also includes authentication support and automated tests for key application behavior. It is best used as an educational reference or starting point rather than a maintained production template. ... -
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PicMo
JavaScript emoji picker. Any app, any framework
Plain JavaScript emoji picker. Any app, any framework. Use PicMo to add a rich emoji picker to any JavaScript project, regardless of the framework. Use the platform's native emojis, or cross-platform emojis from Twemoji. Even add your own custom emojis and GIFs. Search for emojis by name or tags. Customize sizing, layout, and UI elements. Emoji data is loaded once from a CDN and cached in the browser for subsequent sessions. -
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Kinetic.jl
Universal modeling and simulation of fluid mechanics upon ML
Kinetic is a computational fluid dynamics toolbox written in Julia. It aims to furnish efficient modeling and simulation methodologies for fluid dynamics, augmented by the power of machine learning. Based on differentiable programming, mechanical and neural network models are fused and solved in a unified framework. Simultaneous 1-3 dimensional numerical simulations can be performed on CPUs and GPUs. -
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fastMRI
A large open dataset + tools to speed up MRI scans using ML
...By enabling reconstruction of high-fidelity MR images from significantly fewer measurements, fastMRI aims to make MRI scanning faster, cheaper, and more accessible in clinical settings. The repository provides an open-source PyTorch framework with data loaders, subsampling utilities, reconstruction models, and evaluation metrics, supporting both research reproducibility and practical experimentation. It includes reference implementations for key MRI reconstruction architectures such as U-Net and Variational Networks (VarNet), along with example scripts for model training and evaluation using the PyTorch Lightning framework. ... -
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PromethAI
Open-source framework that gives you AI Agents
PromethAI-Backend is a backend framework for AI-driven automation and knowledge extraction. It is designed to integrate with large language models (LLMs) to provide AI-enhanced workflows, including content generation, summarization, and data analysis. -
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Lightning Flash
Flash enables you to easily configure and run complex AI recipes
Your PyTorch AI Factory, Flash enables you to easily configure and run complex AI recipes for over 15 tasks across 7 data domains. In a nutshell, Flash is the production-grade research framework you always dreamed of but didn't have time to build. All data loading in Flash is performed via a from_* classmethod on a DataModule. Which DataModule to use and which from_* methods are available depends on the task you want to perform. For example, for image segmentation where your data is stored in folders, you would use the from_folders method of the SemanticSegmentationData class. ... -
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TXM
Unicode XML TEI text analysis platform
TXM is a free and open-source cross-platform Unicode & XML based text analysis environment and graphical client, supporting Windows, Linux and Mac OS X. It can also be used online as a J2EE standard compliant web portal (GWT based) with access control built in. DOWNLOAD LATEST VERSION OF TXM : http://textometrie.ens-lyon.fr/spip.php?rubrique61&lang=en TXM offers a comprehensive range of analysis tools (concordances, collocate search, frequency lists, etc.) based on the powerfull CQP... -
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Horovod
Distributed training framework for TensorFlow, Keras, PyTorch, etc.
...Horovod can be installed on-premise or run out-of-the-box in cloud platforms, including AWS, Azure, and Databricks. Horovod can additionally run on top of Apache Spark, making it possible to unify data processing and model training into a single pipeline. Once Horovod has been configured, the same infrastructure can be used to train models with any framework, making it easy to switch between TensorFlow, PyTorch, MXNet, and future frameworks as machine learning tech stacks continue to evolve. Start scaling your model training with just a few lines of Python code. ... -
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Metaseq
Repo for external large-scale work
Metaseq is a flexible, high-performance framework for training and serving large-scale sequence models, such as language models, translation systems, and instruction-tuned LLMs. Built on top of PyTorch, it provides distributed training, model sharding, mixed-precision computation, and memory-efficient checkpointing to support models with hundreds of billions of parameters. The framework was used internally at Meta to train models like OPT (Open Pre-trained Transformer) and serves as a reference implementation for scaling transformer architectures efficiently across GPUs and nodes. ... -
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DpdlScripting
DPDL (Dynamic Packet Definition Language) is a small framework library
Dpdl (Dynamic Packet Definition Language) is a constraint device framework and scripting engine that can be used to implement small, portable and light-weight applications on Java enabled devices (in particular J2ME and JavaME) and small embedded systems. It has been developed in 2002, in early days when mobile phones where running mostly J2ME applications. Dpdl is a compact framework, small memory footprint library and scripting engine that can be used to encode, decode, control and query data efficiently on limited memory devices. ... -
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aqueduct LLM
Aqueduct allows you to run LLM and ML workloads on any infrastructure
Aqueduct is an MLOps framework that allows you to define and deploy machine learning and LLM workloads on any cloud infrastructure. Aqueduct is an open-source MLOps framework that allows you to write code in vanilla Python, run that code on any cloud infrastructure you'd like to use, and gain visibility into the execution and performance of your models and predictions. Aqueduct's Python native API allows you to define ML tasks in regular Python code. You can connect Aqueduct to your existing... -
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iJEPA
Official codebase for I-JEPA
...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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AB3DMOT
Official Python Implementation for "3D Multi-Object Tracking
AB3DMOT is a real-time 3D multi-object tracking framework designed for applications such as autonomous driving and robotics perception. The system processes detection results from 3D object detectors that analyze LiDAR point clouds and uses them to track multiple objects across consecutive frames. Its tracking pipeline relies on a combination of classical algorithms, including a Kalman filter for state estimation and the Hungarian algorithm for data association between detected objects and existing tracks. ... -
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langchain-prefect
Tools for using Langchain with Prefect
...We need to know details about how our apps work, even when we want to use tools with convenient abstractions that may obfuscate those details. Prefect is built to help data people build, run, and observe event-driven workflows wherever they want. It provides a framework for creating deployments on a whole slew of runtime environments (from Lambda to Kubernetes), and is cloud agnostic (best supports AWS, GCP, Azure). For this reason, it could be a great fit for observing apps that use LLMs. RecordLLMCalls is a ContextDecorator that can be used to track LLM calls made by Langchain LLMs as Prefect flows. ... -
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Network Instrument Workbench
Script driven framework for Prologix GPIB - Lan adapter & more
A layered set of functions to abstract the Prologix command set into an easy to use bash shell script format. To provide access to and control of electronic test equipment, initially for data logging applications. Functions to configure, send commands, data and status. Also to provides functionality for direct access to other network enabled equipment. Command line and makefile environment. Developed under FreeBSD, but built and tested without code change under Debian, XUbuntu and Devuan Linux. Overall, the aim is to provide some of the control functionality and simplicity of the old HP Basic instrument control framework, accessable from any machine on the network. ... -
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FluentLenium
FluentLenium is a web & mobile automation framework
FluentLenium is a React-ready website automation framework that extends Selenium to write readable, reusable, reliable and resilient UI functional tests. It’s written and maintained by people who are automating browser-based tests on a daily basis. FluentLenium provides a Java-fluent interface to Selenium, and brings some magic to avoid common issues faced by Selenium users. FluentLenium is shipped with adapters for JUnit4, JUnit5, TestNG, Spock, Spring TestNG, Cucumber and Kotest, but it... -
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Spektral
Graph Neural Networks with Keras and Tensorflow 2
Spektral is a Python library for graph deep learning, based on the Keras API and TensorFlow 2. The main goal of this project is to provide a simple but flexible framework for creating graph neural networks (GNNs). You can use Spektral for classifying the users of a social network, predicting molecular properties, generating new graphs with GANs, clustering nodes, predicting links, and any other task where data is described by graphs. Spektral implements some of the most popular layers for graph deep learning. ... -
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The Related Values Processing Framework helps the integration of Process Control Data Historian Systems.
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crawly
High-level web crawling and scraping framework for Elixir apps
Crawly is a high-level application framework for crawling websites and extracting structured data using the Elixir programming language. It provides a complete environment for building web crawlers that systematically visit pages, collect information, and transform that data into structured formats for further processing. Crawly is designed for tasks such as data mining, information processing, and building historical archives of web content. -
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AI-Agent-Host
The AI Agent Host is a module-based development environment.
...The AI Agent Host is a module-based environment designed to facilitate rapid experimentation and testing. It includes a docker-compose configuration with QuestDB, Grafana, Code-Server and Nginx. The AI Agent Host provides a seamless interface for managing and querying data, visualizing results, and coding in real-time. The AI Agent Host is built specifically for LangChain, a framework dedicated to developing applications powered by language models. LangChain recognizes that the most powerful and distinctive applications go beyond simply utilizing a language model and strive to be data-aware and agentic. ... -
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OpenCombine
Open source implementation of Apple's Combine framework
OpenCombine is an open-source implementation of Apple’s Combine framework, providing a reactive programming model for handling asynchronous data streams in Swift across multiple platforms. It replicates the core concepts of Combine, such as publishers, subscribers, and operators, enabling developers to process values over time in a declarative and composable way. One of its primary goals is compatibility, allowing developers to use Combine-like APIs on platforms where Apple’s official implementation is unavailable, including older Apple operating systems, Linux, Windows, and WebAssembly environments. ... -
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Matrix
Plugin style, non-invasive APM system developed by WeChat
...The monitoring scope of the current tool includes: crash, lag, and out-of-memory, which includes the following two plugins, WCCrashBlockMonitorPlugin, which is based on KSCrash framework and features cutting-edge lag stack capture capabilities with crash capture, and WCMemoryStatPlugin, which is a performance-optimized out-of-memory monitoring tool that captures memory allocation and the callstack of an application's out-of-memory event. Determine whether the app is stuck by checking the running status of the Runloop, and support both the iOS and macOS platform. ... -
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Hippo4j
Powerful dynamic thread pool framework with monitoring/alarm functions
Dynamically observable thread pool framework to improve online operation guarantee capabilities for business systems. Dynamically change thread pool parameters when the application is running, including not limited to core, maximum thread, blocking queue size, and rejection strategy, etc., and support different node thread pool configuration differentiation under the application cluster. -
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4WS Warp
Development of extjs based rich web applications
Warp is an open source framework that can be used to develop Java based applications, using Java and JEE5. It allows to develop Desktop Applications or 3 Tier Applications based on Swing extensions or Rich web applications based on ExtJS and JAX-RS (Restful web services). Business logic and data access tiers can be developed using JPA or JDBC and EJB 3 or any other Java based technology.
