Showing 11 open source projects for "data processing"

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    Kinetic Software - Epicor ERP

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  • 1
    WiFi DensePose

    WiFi DensePose

    Turn WiFi signals into real-time human pose estimation and detection

    WiFi DensePose is a production-oriented implementation of a WiFi-based human pose estimation system that enables real-time full-body tracking using wireless signals rather than cameras. The project demonstrates how commodity mesh routers and signal processing techniques can be leveraged to infer dense human pose information, even through obstacles such as walls. It is designed to showcase the emerging field of RF-based sensing, where machine learning models interpret wireless channel data to reconstruct human movement and posture. The repository includes components for data processing, model inference, and real-time visualization, making it suitable for research and experimental deployments. ...
    Downloads: 53 This Week
    Last Update:
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  • 2
    Jina

    Jina

    Build cross-modal and multimodal applications on the cloud

    Jina is a framework that empowers anyone to build cross-modal and multi-modal applications on the cloud. It uplifts a PoC into a production-ready service. Jina handles the infrastructure complexity, making advanced solution engineering and cloud-native technologies accessible to every developer. Build applications that deliver fresh insights from multiple data types such as text, image, audio, video, 3D mesh, PDF with Jina AI’s DocArray. Polyglot gateway that supports gRPC, Websockets, HTTP,...
    Downloads: 0 This Week
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  • 3
    CloudI: A Cloud at the lowest level
    CloudI is an open-source private cloud computing framework for efficient, secure, and internal data processing. CloudI provides scaling for previously unscalable source code with efficient fault-tolerant execution of ATS, C/C++, Erlang/Elixir, Go, Haskell, Java, JavaScript/node.js, OCaml, Perl, PHP, Python, Ruby, or Rust services. The bare essentials for efficient fault-tolerant processing on a cloud!
    Downloads: 7 This Week
    Last Update:
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  • 4
    SageMaker Experiments Python SDK

    SageMaker Experiments Python SDK

    Experiment tracking and metric logging for Amazon SageMaker notebooks

    ...Each step in the workflow is described by a Trial Component. There is no relationship between Trial Components such as ordering. Trial Component: A description of a single step in a machine learning workflow. For example data cleaning, feature extraction, model training, model evaluation, etc.
    Downloads: 0 This Week
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  • Secure Online Fax and Business Text Messaging Service Icon
    Secure Online Fax and Business Text Messaging Service

    Elevate your business communications with secure SMS and fax solutions.

    Send and receive SMS and fax online, from email, app or with our developer friendly SMS & fax API. HIPAA compliant & ISO 27001 certified. Outstanding value and 5-star service.
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  • 5
    GXSM

    GXSM

    Scanning Probe Microscopy Controller and Data Visualization Software

    GXSM -- Gnome X Scanning Microscopy: A multi-channel image and vector-probe data acquisition and visualization system designed for SPM techniques (STM,AFM..), but also SPA-LEED/LEED/LEEM data analysis. A plug-in interface allows any user add-on data-processing and special hardware and instrument support. Latest: NC-AFM and related explorative methods as SQDM can be configured. High-Speed external PAC-PLL hardware option with digital DSP link.
    Downloads: 8 This Week
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  • 6

    dispy

    Distributed and Parallel Computing with/for Python.

    dispy is a generic and comprehensive, yet easy to use framework for creating and using compute clusters to execute computations in parallel across multiple processors in a single machine (SMP), among many machines in a cluster, grid or cloud. dispy is well suited for data parallel (SIMD) paradigm where a computation (Python function or standalone program) is evaluated with different (large) datasets independently. dispy supports public / private / hybrid cloud computing, fog / edge computing.
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    Downloads: 13 This Week
    Last Update:
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  • 7
    A set of tools (command line and GUI) to provide a complete digital photo workflow for Unixes. EXIF headers are used as the central information repository, so users may change their software at any time without loosing any data.
    Downloads: 7 This Week
    Last Update:
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  • 8
    Albedo

    Albedo

    A recommender system for discovering GitHub repos

    ...It treats repositories and developers as a graph of interactions and applies large-scale matrix factorization to model affinities, with Apache Spark providing the distributed data processing. The project focuses on implicit feedback—stars, watches, and other engagement metrics—so it can build useful recommendations without explicit ratings. A reproducible setup and Makefile-driven workflow streamline tasks like spinning up services, loading datasets, training models, and generating candidate lists. Because it’s built around Spark’s scalable primitives, Albedo can experiment on substantial snapshots of GitHub metadata rather than toy corpora. ...
    Downloads: 0 This Week
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  • 9
    jsondata

    jsondata

    Modular JSON by trees and branches, pointers and patches

    The 'jsondata' package provides for the modular in-memory processing of JSON data by trees, branches, pointers, and patches. The main interface classes are: - JSONData - Core for RFC7159 based data structures. Provides modular data components. - JSONDataSerializer - Core for RFC7159 based data persistence. Provides modular data serialization. - JSONPointer - RFC6901 for addressing by pointer paths.
    Downloads: 0 This Week
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    Construction Takeoff Software

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  • 10

    Hierarchical cluster engine HCE

    Hierarchical Cluster Engine project

    The main idea of this project – to implement the solution that can be used to: construct custom network mesh or distributed network cluster structure with several relations types between nodes, formalize the data flow processing goes from upper node level central source point to down nodes and backward, formalize the management requests handling from multiple source points, support native reducing of multiple nodes results (aggregation, duplicates elimination, sorting and so on), internally support powerful full-text search engine and data storage, provide transactions-less and transactional requests processing, support flexible run-time changes of cluster infrastructure, have many languages bindings for client-side integration APIs in one product build on C++ language... ...
    Downloads: 0 This Week
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  • 11
    StreamMine is a distributed event processing (streaming) infrastructure. You can create low-latency, fault-tolerant stream processing functionality with any stream-oriented operators that can be implemented in Python.
    Downloads: 0 This Week
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