Showing 7 open source projects for "compiler python linux"

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  • 1
    Label Studio

    Label Studio

    Label Studio is a multi-type data labeling and annotation tool

    The most flexible data annotation tool. Quickly installable. Build custom UIs or use pre-built labeling templates. Detect objects on image, bboxes, polygons, circular, and keypoints supported. Partition image into multiple segments. Use ML models to pre-label and optimize the process. Label Studio is an open-source data labeling tool. It lets you label data types like audio, text, images, videos, and time series with a simple and straightforward UI and export to various model formats. It can...
    Downloads: 12 This Week
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  • 2
    Toloka-Kit

    Toloka-Kit

    Toloka-Kit is a Python library for working with Toloka API

    Toloka-Kit is a Python library for working with Toloka API. The API allows you to build scalable and fully automated human-in-the-loop ML pipelines, and integrate them into your processes. The toolkit makes integration easier. You can use it with Jupyter Notebooks. Support for all common Toloka use cases: creating projects, adding pools, uploading tasks, and so on. Toloka entities are represented as Python classes. You can use them instead of accessing the API using JSON representations...
    Downloads: 1 This Week
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  • 3
    Lightly

    Lightly

    A python library for self-supervised learning on images

    ... through advanced filtering. We provide PyTorch, PyTorch Lightning and PyTorch Lightning distributed examples for each of the models to kickstart your project. Lightly requires Python 3.6+ but we recommend using Python 3.7+. We recommend installing Lightly in a Linux or OSX environment. With lightly, you can use the latest self-supervised learning methods in a modular way using the full power of PyTorch. Experiment with different backbones, models, and loss functions.
    Downloads: 0 This Week
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  • 4
    Compose

    Compose

    A machine learning tool for automated prediction engineering

    Compose is a machine learning tool for automated prediction engineering. It allows you to structure prediction problems and generate labels for supervised learning. An end user defines an outcome of interest by writing a labeling function, then runs a search to automatically extract training examples from historical data. Its result is then provided to Featuretools for automated feature engineering and subsequently to EvalML for automated machine learning. Prediction problems are structured...
    Downloads: 0 This Week
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  • 5
    Cleanlab

    Cleanlab

    The standard data-centric AI package for data quality and ML

    cleanlab helps you clean data and labels by automatically detecting issues in a ML dataset. To facilitate machine learning with messy, real-world data, this data-centric AI package uses your existing models to estimate dataset problems that can be fixed to train even better models. cleanlab cleans your data's labels via state-of-the-art confident learning algorithms, published in this paper and blog. See some of the datasets cleaned with cleanlab at labelerrors.com. This package helps you...
    Downloads: 0 This Week
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  • 6
    Diffgram

    Diffgram

    Training data (data labeling, annotation, workflow) for all data types

    From ingesting data to exploring it, annotating it, and managing workflows. Diffgram is a single application that will improve your data labeling and bring all aspects of training data under a single roof. Diffgram is world’s first truly open source training data platform that focuses on giving its users an unlimited experience. This is aimed to reduce your data labeling bills and increase your Training Data Quality. Training Data is the art of supervising machines through data. This...
    Downloads: 0 This Week
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  • 7
    bbox-visualizer

    bbox-visualizer

    Make drawing and labeling bounding boxes easy as cake

    Make drawing and labeling bounding boxes easy as cake. This package helps users draw bounding boxes around objects, without doing the clumsy math that you'd need to do for positioning the labels. It also has a few different types of visualizations you can use for labeling objects after identifying them. There are optional functions that can draw multiple bounding boxes and/or write multiple labels on the same image, but it is advisable to use the above functions in a loop in order to have...
    Downloads: 0 This Week
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