Showing 4 open source projects for "python data analysis"

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  • Jscrambler: Pioneering Client-Side Protection Platform Icon
    Jscrambler: Pioneering Client-Side Protection Platform

    Jscrambler offers an exclusive blend of cutting-edge first-party JavaScript obfuscation and state-of-the-art third-party tag protection.

    Jscrambler is the leader in Client-Side Protection and Compliance. We were the first to merge advanced polymorphic JavaScript obfuscation with fine-grained third-party tag protection in a unified Client-Side Protection and Compliance Platform. Our integrated solution ensures a robust defense against current and emerging client-side cyber threats, data leaks, and IP theft, empowering software development and digital teams to innovate securely. With Jscrambler, businesses adopt a unified, future-proof client-side security policy all while achieving compliance with emerging security standards including PCI DSS v4.0. Trusted by digital leaders worldwide, Jscrambler gives businesses the freedom to innovate securely.
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  • QA Wolf | We Write, Run and Maintain Tests Icon
    QA Wolf | We Write, Run and Maintain Tests

    For developer teams searching for a testing software

    QA Wolf is an AI-native service that delivers 80% automated E2E test coverage for web & mobile apps in weeks not years.
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  • 1
    pyntcloud

    pyntcloud

    pyntcloud is a Python library for working with 3D point clouds

    This page will introduce the general concept of point clouds and illustrate the capabilities of pyntcloud as a point cloud processing tool. Point clouds are one of the most relevant entities for representing three dimensional data these days, along with polygonal meshes (which are just a special case of point clouds with connectivity graph attached). In its simplest form, a point cloud is a set of points in a cartesian coordinate system. Accurate 3D point clouds can nowadays be (easily and...
    Downloads: 1 This Week
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  • 2
    Pytorch Points 3D

    Pytorch Points 3D

    Pytorch framework for doing deep learning on point clouds

    Torch Points 3D is a framework for developing and testing common deep learning models to solve tasks related to unstructured 3D spatial data i.e. Point Clouds. The framework currently integrates some of the best-published architectures and it integrates the most common public datasets for ease of reproducibility. It heavily relies on Pytorch Geometric and Facebook Hydra library thanks for the great work! We aim to build a tool that can be used for benchmarking SOTA models, while also allowing practitioners to efficiently pursue research into point cloud analysis, with the end goal of building models which can be applied to real-life applications. ...
    Downloads: 0 This Week
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  • 3
    Objectron

    Objectron

    A dataset of short, object-centric video clips

    The Objectron dataset is a collection of short, object-centric video clips, which are accompanied by AR session metadata that includes camera poses, sparse point-clouds and characterization of the planar surfaces in the surrounding environment. In each video, the camera moves around the object, capturing it from different angles. The data also contain manually annotated 3D bounding boxes for each object, which describe the object’s position, orientation, and dimensions. The dataset consists...
    Downloads: 0 This Week
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  • 4
    XIVO

    XIVO

    X Inertial-aided Visual Odometry

    XIVO is an open-source repository for visual-inertial odometry/mapping. It is a simplified version of Corvis [Jones et al.,Tsotsos et al.], designed for pedagogical purposes, and incorporates odometry (relative motion of the sensor platform), local mapping (pose relative to a reference frame of the oldest visible features), and global mapping (pose relative to a global frame, including loop-closure and global re-localization, this feature, present in Corvis, is not yet incorporated in XIVO)....
    Downloads: 0 This Week
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  • Unrivaled Embedded Payments Solutions | NMI Icon
    Unrivaled Embedded Payments Solutions | NMI

    For SaaS builders, software companies, ISVs and ISOs who want to embed payments into their tech stack

    NMI Payments is an embedded payments solution that lets SaaS platforms, Software companies and ISVs integrate, brand, and manage payment acceptance directly within their software—without becoming a PayFac or building complex infrastructure. As a full-stack processor, acquirer, and technology partner, NMI handles onboarding, compliance, and risk so you can stay focused on growth. The modular, white-label platform supports omnichannel payments, from online, mobile and in-app to in-store and unattended. Choose from full-code, low-code, or no-code integration paths and launch in weeks, not months. Built-in risk tools, flexible monetization, and customizable branding help you scale faster while keeping full control of your experience. With NMI’s developer-first tools, sandbox testing, and modern APIs, you can embed payments quickly and confidently.
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