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Source channel @githubtrending · Post #15043 · Aug 9

#go#2fa#authentication#caddy#golang#middleware#nginx#selfhosted#sso#totp#traefik_middleware#typescipt Tinyauth is a simple tool that adds a login screen or OAuth login (Google, Github, etc.) to your Docker apps, making them secure easily. It works with popular reverse proxies like Traefik, Nginx, and Caddy. You can quickly set it up using their documentation and demo, and it supports basic authentication and API access. This helps protect your apps from unauthorized access without complex setup. It’s open source, actively developed, and has a helpful community on Discord for support. Using Tinyauth improves your app security with minimal effort and flexible login options. https://github.com/steveiliop56/tinyauth

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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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