Showing 4 open source projects for "human"

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  • 1
    pydna

    pydna

    Clone with Python! Data structures for double stranded DNA

    ...Planning genetic constructs with many parts and assembly steps, such as recombinant metabolic pathways, are often difficult to properly document as is evident from the poor state of documentation in the scientific literature. The pydna python package provide a human-readable formal description of cloning and genetic assembly strategies in Python which allow for simulation and verification. Pydna can be used as executable documentation for cloning.
    Downloads: 0 This Week
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  • 2
    PySyft

    PySyft

    Data science on data without acquiring a copy

    ...However, this means that you cannot compute on information without first obtaining (at least partial) ownership of that information. It also means that you cannot compute using machines without first obtaining control over those machines. This is very limiting to human collaboration and systematically drives the centralization of data, because you cannot work with a bunch of data without first putting it all in one (central) place. The Syft ecosystem seeks to change this system, allowing you to write software which can compute over information you do not own on machines you do not have (total) control over. ...
    Downloads: 1 This Week
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  • 3

    PLplot

    Cross-platform, scientific graphics plotting library

    PLplot is a cross-platform, scientific graphics plotting library that supports math symbols and human languages (via UTF-8 user input strings); plot capabilities for multiple non-interactive plot file formats and in multiple interactive environments; and bindings for multiple computer languages.
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    Downloads: 59 This Week
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  • 4
    TransPose

    TransPose

    PyTorch Implementation for "TransPose, Keypoint localization

    TransPose is a human pose estimation model based on a CNN feature extractor, a Transformer Encoder, and a prediction head. Given an image, the attention layers built in Transformer can efficiently capture long-range spatial relationships between keypoints and explain what dependencies the predicted keypoints locations highly rely on.
    Downloads: 5 This Week
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