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tfjs - A WebGL accelerated, browser based JavaScript library for training and deploying ML models.


TensorFlow.js is an open-source hardware-accelerated JavaScript library for training and deploying machine learning models. Develop ML in the Browser Use flexible and intuitive APIs to build models from scratch using the low-level JavaScript linear algebra library or the high-level layers API.

tfjs-core - WebGL-accelerated ML // linear algebra // automatic differentiation for JavaScript.


NOTE: Building on the momentum of deeplearn.js, we have joined the TensorFlow family and we are starting a new ecosystem of libraries and tools for Machine Learning in Javascript, called TensorFlow.js. This repo moved from PAIR-code/deeplearnjs to tensorflow/tfjs-core. A part of the TensorFlow.js ecosystem, this repo hosts @tensorflow/tfjs-core, the TensorFlow.js Core API, which provides low-level, hardware-accelerated linear algebra operations and an eager API for automatic differentiation.

matrix-to-css - Converts gl-matrix mat4 objects into css transform: matrix3d strings


Converts gl-matrix(1) mat4 objects into strings that can be applied as values for css transform properties on elements. Because if you move elements using...

RPIMotionDetection - Blob detection library with example applications


If you compile on the RPi: Please note that the compiling of the release version (-O3) requires a big amount of memory. If the compiling fails reduce the memory for the gpu at 64MB (config.txt) or enable swapping. If you compile on other systems: Add the cmake flag -DWITH_RPI=0 to disable the parts which requires RPi dependecies.




AnvilKit - AnvilKit tames Metal. Very much WIP.


AnvilKit tames Metal. It's a collection of code that seems to come up in just about every project that everyone seems to roll themselves. Object that wraps MTLDevice and makes it into a singleton so that you don't need to pass it around.