Showing 4 open source projects for "work"

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  • 1
    NSFWJS

    NSFWJS

    Client-side indecent content checking powered by TensorFlow.js

    ...It is powered by TensorFlow.js and the NSFW detection model, and delivers around 90% accuracy that is improving each time. NSFWJS classifies images with percentages under five categories, namely: drawing and neutral, which are both safe for work; sexy, which includes sexually explicit images; and hentai and porn, which are pornographic drawings and images. NSFWJS offers a 'browserified' version, an NSFW filter web extension that filters out NSFW images from your browser, and also has a separate React Native app.
    Downloads: 2 This Week
    Last Update:
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  • 2
    Face Alignment

    Face Alignment

    2D and 3D Face alignment library build using pytorch

    ...However, the users can alternatively use dlib, BlazeFace, or pre-existing ground truth bounding boxes. While not required, for optimal performance(especially for the detector) it is highly recommended to run the code using a CUDA-enabled GPU. While here the work is presented as a black box, if you want to know more about the intrisecs of the method please check the original paper either on arxiv or my webpage.
    Downloads: 4 This Week
    Last Update:
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  • 3
    Exadel CompreFace

    Exadel CompreFace

    Leading free and open-source face recognition system

    ...The solution also features a role management system that allows you to easily control who has access to your Face Recognition Services. CompreFace is delivered as a docker-compose config and supports different models that work on CPU and GPU. Our solution is based on state-of-the-art methods and libraries like FaceNet and InsightFace. Official website: https://exadel.com/solutions/compreface/ Github link: https://github.com/exadel-inc/CompreFace
    Downloads: 10 This Week
    Last Update:
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  • 4
    clmtrackr

    clmtrackr

    Javascript library for precise tracking of facial features

    ...The library provides some generic face models that were trained on the MUCT database and some additional self-annotated images. Check out clmtools for building your own models. For tracking in video, it is recommended to use a browser with WebGL support, though the library should work on any modern browser. For some more information about Constrained Local Models, take a look at Xiaoguang Yan's excellent tutorial, which was of great help in implementing this library.
    Downloads: 0 This Week
    Last Update:
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