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Source channel @githubtrending · Post #15365 · Dec 24

#jupyter_notebook DINOv3 offers powerful self-supervised vision models from Meta AI, like ViT up to 7B parameters and ConvNeXt, pretrained on 1.7B web or satellite images. Load them easily via PyTorch Hub, Hugging Face Transformers (v4.56+), or timm (v1.0.20+), with code examples for features, depth, detection, and segmentation. You benefit by using these top-performing, dense features without fine-tuning or labels—saving time and compute for tasks like classification, object detection, and zero-shot analysis on your images. https://github.com/facebookresearch/dinov3

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Architectural Shovel / Любовь Дмитриева

@arch_shovel · Post #663 · 09/07/2022, 08:31 PM

C U R V E S / Under Magnitude by Marc Fornes / THEVERYMANY The strength of #undermagnitude is achieved by 'Intensive Curvature,' which is the maximization of double #curvature across the project while constraining maximum radii. The result is a #structure that has much tighter curvature with constant change of direction, and results in more structurally performance. 'Intensive Curvature' leads to the curly, tubular branching characteristics consistent across the studio's body of work. In order to achieve structural #stability , each stripe assumes high degrees of curvature individually and high degrees of double curvature in accumulation -- amounting to extreme structural #rigidity throughout the project. #arch_shovel#archdaily