Showing 11 open source projects for "open-capwap"

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  • 1
    Mimesis

    Mimesis

    High-performance fake data generator for Python

    Mimesis is an open source high-performance fake data generator for Python, able to provide data for various purposes in various languages. It's currently the fastest fake data generator for Python, and supports many different data providers that can produce data related to people, food, transportation, internet and many more. Mimesis is really easy to use, with everything you need just an import away.
    Downloads: 3 This Week
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  • 2
    BlenderProc

    BlenderProc

    Blender pipeline for photorealistic training image generation

    A procedural Blender pipeline for photorealistic training image generation. BlenderProc has to be run inside the blender python environment, as only there we can access the blender API. Therefore, instead of running your script with the usual python interpreter, the command line interface of BlenderProc has to be used. In general, one run of your script first loads or constructs a 3D scene, then sets some camera poses inside this scene and renders different types of images (RGB, distance,...
    Downloads: 1 This Week
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  • 3
    Copulas

    Copulas

    A library to model multivariate data using copulas

    Copulas is a Python library for modeling multivariate distributions and sampling from them using copula functions. Given a table of numerical data, use Copulas to learn the distribution and generate new synthetic data following the same statistical properties. Choose from a variety of univariate distributions and copulas – including Archimedian Copulas, Gaussian Copulas and Vine Copulas. Compare real and synthetic data visually after building your model. Visualizations are available as 1D...
    Downloads: 0 This Week
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  • 4
    Synthetic Data Kit

    Synthetic Data Kit

    Tool for generating high quality Synthetic datasets

    Synthetic Data Kit is a CLI-centric toolkit for generating high-quality synthetic datasets to fine-tune Llama models, with an emphasis on producing reasoning traces and QA pairs that line up with modern instruction-tuning formats. It ships an opinionated, modular workflow that covers ingesting heterogeneous sources (documents, transcripts), prompting models to create labeled examples, and exporting to fine-tuning schemas with minimal glue code. The kit’s design goal is to shorten the “data...
    Downloads: 0 This Week
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  • 5
    Gretel Synthetics

    Gretel Synthetics

    Synthetic data generators for structured and unstructured text

    Unlock unlimited possibilities with synthetic data. Share, create, and augment data with cutting-edge generative AI. Generate unlimited data in minutes with synthetic data delivered as-a-service. Synthesize data that are as good or better than your original dataset, and maintain relationships and statistical insights. Customize privacy settings so that data is always safe while remaining useful for downstream workflows. Ensure data accuracy and privacy confidently with expert-grade reports....
    Downloads: 0 This Week
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  • 6
    YData Synthetic

    YData Synthetic

    Synthetic data generators for tabular and time-series data

    A package to generate synthetic tabular and time-series data leveraging state-of-the-art generative models. Synthetic data is artificially generated data that is not collected from real-world events. It replicates the statistical components of real data without containing any identifiable information, ensuring individuals' privacy. This repository contains material related to Generative Adversarial Networks for synthetic data generation, in particular regular tabular data and time-series. It...
    Downloads: 0 This Week
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  • 7
    Synthetic Data Vault (SDV)

    Synthetic Data Vault (SDV)

    Synthetic Data Generation for tabular, relational and time series data

    The Synthetic Data Vault (SDV) is a Synthetic Data Generation ecosystem of libraries that allows users to easily learn single-table, multi-table and timeseries datasets to later on generate new Synthetic Data that has the same format and statistical properties as the original dataset. Synthetic data can then be used to supplement, augment and in some cases replace real data when training Machine Learning models. Additionally, it enables the testing of Machine Learning or other data dependent...
    Downloads: 0 This Week
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  • 8
    SDGym

    SDGym

    Benchmarking synthetic data generation methods

    The Synthetic Data Gym (SDGym) is a benchmarking framework for modeling and generating synthetic data. Measure performance and memory usage across different synthetic data modeling techniques – classical statistics, deep learning and more! The SDGym library integrates with the Synthetic Data Vault ecosystem. You can use any of its synthesizers, datasets or metrics for benchmarking. You also customize the process to include your own work. Select any of the publicly available datasets from the...
    Downloads: 0 This Week
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  • 9
    Zylthra

    Zylthra

    Zylthra: A PyQt6 app to generate synthetic datasets with DataLLM.

    Welcome to Zylthra, a powerful Python-based desktop application built with PyQt6, designed to generate synthetic datasets using the DataLLM API from data.mostly.ai. This tool allows users to create custom datasets by defining columns, configuring generation parameters, and saving setups for reuse, all within a sleek, dark-themed interface.
    Downloads: 1 This Week
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    AI-generated apps that pass security review

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    Retool 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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  • 10
    Tofu

    Tofu

    Tofu is a Python tool for generating synthetic UK Biobank data

    Tofu is a Python library for generating synthetic UK Biobank data. The UK Biobank is a large open-access prospective research cohort study of 500,000 middle-aged participants recruited in England, Scotland and Wales. The study has collected and continues to collect extensive phenotypic and genotypic detail about its participants, including data from questionnaires, physical measures, sample assays, accelerometry, multimodal imaging, genome-wide genotyping and longitudinal follow-up for a wide range of health-related outcomes. ...
    Downloads: 0 This Week
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  • 11
    TGAN

    TGAN

    Generative adversarial training for generating synthetic tabular data

    We are happy to announce that our new model for synthetic data called CTGAN is open-sourced. The new model is simpler and gives better performance on many datasets. TGAN is a tabular data synthesizer. It can generate fully synthetic data from real data. Currently, TGAN can generate numerical columns and categorical columns. TGAN has been developed and runs on Python 3.5, 3.6 and 3.7. Also, although it is not strictly required, the usage of a virtualenv is highly recommended in order to avoid interfering with other software installed in the system where TGAN is run. ...
    Downloads: 0 This Week
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