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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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MessageInABottle

@mib_messageinabottle · Post #6953 · 05/26/2024, 12:59 PM

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🇬🇧#UK #PreCrime "I WAS MISIDENTIFIED AS SHOPLIFTER BY FACIAL RECOGNITION TECH" Sara needed some chocolate - she had had one of those days - so wandered into a #HomeBargains store. "Within less than a minute, I'm approached by a store worker who comes up to me and says, 'You're a thief, you need to leave the store'." Sara - who wants to remain anonymous - was wrongly accused after being flagged by a facial-recognition system called #Facewatch. She says after her bag was searched she was led out of the shop, and told she was banned from all stores using the technology. Facewatch later wrote to Sara and acknowledged it had made an error. The #MetropolitanPolice in #London say that around one in every 33,000 people who walk by its cameras is misidentified. But the error count is much higher once someone is actually flagged. One in 40 alerts so far this year has been a false positive #AI #FacialRecognition

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