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Segment Anything Model and Dataset (SAM and SA-1B): Difference between revisions
Segment Anything Model and Dataset (SAM and SA-1B) (view source)
Revision as of 15:16, 9 April 2023
, 9 April 2023→Promptable Segmentation
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===Promptable Segmentation=== | ===Promptable Segmentation=== | ||
[[File:segment anything model2.png|400px|right]] | |||
SAM is designed to return a valid segmentation mask for any [[prompt]], whether it be foreground/background points, a rough box or mask, freeform text, or any other information indicating what to segment in an image. This model has been trained on the SA-1B dataset, which consists of over 1 billion masks, allowing it to generalize to new objects and images beyond its [[training data]]. As a result, practitioners no longer need to collect their own segmentation data and [[fine-tune]] a model for their use case. | SAM is designed to return a valid segmentation mask for any [[prompt]], whether it be foreground/background points, a rough box or mask, freeform text, or any other information indicating what to segment in an image. This model has been trained on the SA-1B dataset, which consists of over 1 billion masks, allowing it to generalize to new objects and images beyond its [[training data]]. As a result, practitioners no longer need to collect their own segmentation data and [[fine-tune]] a model for their use case. | ||