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Source channel @githubtrending · Post #14627 · Apr 24

#jupyter_notebook DINOv2 is a powerful AI model from Meta AI that learns to understand images without needing labeled data, using self-supervised learning. It was trained on 142 million images and creates strong visual features that work well for many tasks like image classification, depth estimation, and segmentation without extra fine-tuning. You can use its pretrained models easily with simple classifiers, saving time and effort. DINOv2 is efficient, scalable, and performs better than many other models, making it great for building versatile computer vision applications quickly and accurately. It’s open-source and ready to use with PyTorch. https://github.com/facebookresearch/dinov2

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djangoproject

@djangoproject · Post #388 · 07/19/2017, 08:35 PM

https://www.youtube.com/watch?v=D-5V7s0GflU Look mum no hands! From blinking LEDs to a bike speedometer with #MicroPython In this talk I will show you how to use a micro-controller to build a wifi enabled speedometer for your bike, using MicroPython. And some hardware. And a bike (maybe). I will introduce you to the world of MicroPython: a python distribution that runs on micro-controllers. Micro-controllers are small computers that are all around us: in cars, TVs, and your internet connected fridge. We will start with making LEDs blink, then serve webpages, build an interrupt handler and finally put it all together to make a wifi enabled speedometer for a bike.

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djangoproject

@djangoproject · Post #513 · 11/30/2017, 10:00 PM

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