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Source channel @githubtrending · Post #14898 · Jul 2

#javascript#3d#augmented_reality#canvas#html5#javascript#svg#virtual_reality#webaudio#webgl#webgl2#webgpu#webxr Three.js is a powerful and easy-to-use JavaScript library that helps you create 3D graphics and animations on the web with much less code than using WebGL directly. It handles complex tasks like rendering and math calculations, so you can focus on designing your 3D scenes. It supports WebGL and WebGPU, with additional options like SVG and CSS3D. Three.js has excellent documentation, many examples, and a large, active community that provides support and updates. This makes it ideal for quickly building interactive 3D content that works across browsers, improving your web projects with engaging visuals and smooth performance[1][3][5]. https://github.com/mrdoob/three.js

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djangoproject

@djangoproject · Post #274 · 03/18/2017, 01:48 AM

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https://github.com/riga/tfdeploy Google's TensorFlow framework is taking off big-time now that it's at a full 1.0 release. One common question about it: How can I make use of the models I train in TensorFlow without using TensorFlow itself? #Tfdeploy is a partial answer to that question. It exports a trained TensorFlow model to "a simple #NumPy-based callable," meaning the model can be used in Python with Tfdeploy and the the NumPy math-and-stats library as the only dependencies. Most of the operations you can perform in TensorFlow can also be performed in Tfdeploy, and you can extend the behaviors of the library by way of standard Python metaphors (such as overloading a class). Now the bad news: Tfdeploy doesn't support GPU acceleration, if only because NumPy doesn't do that. Tfdeploy's creator suggests using the gNumPy project as a possible replacement. #Machine_learning

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