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Spark in me - Internet, data science, math, deep learning, philosophy

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Spark in me - Internet, data science, math, deep learning, philosophy

3 года назад
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Paper Review: Segment Anything - 99% of masks are automatic, i.e. w/o labels; - Main image encoder model is huge; - To produce masks you need a prompt or a somewhat accurate bbox (partial bbox fails miserably); - Trained on 128 / 256 GPUs; - Most likely - useful a large scale data annotation tool; - Not sure that it can be used in production as is, also license for the dataset is research only, the model is Apache 2.0 https://andlukyane.com//blog/paper-review-sam Unless you have a very specific project (i.e. segment just one object type and you have some priors), this can serve as a decent pre-annotation tool. This is nice, but probably it can offset 10-20% of CV annotation costs.
segment-anything/predictor_example.ipynb at main · facebookresearch/segment-anything

The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model. -...

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