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New AI Model Can 'Cut Out' Any Object Within an Image - Slashdot
source link: https://tech.slashdot.org/story/23/04/06/185247/new-ai-model-can-cut-out-any-object-within-an-image
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New AI Model Can 'Cut Out' Any Object Within an Image
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New AI Model Can 'Cut Out' Any Object Within an Image (arstechnica.com) 8
Posted by msmash
on Thursday April 06, 2023 @02:05PM from the moving-forward dept.
Meta has announced an AI model called the Segment Anything Model (SAM) that can identify individual objects in images and videos, even those not encountered during training. From a report: According to a blog post from Meta, SAM is an image segmentation model that can respond to text prompts or user clicks to isolate specific objects within an image. Image segmentation is a process in computer vision that involves dividing an image into multiple segments or regions, each representing a specific object or area of interest. The purpose of image segmentation is to make an image easier to analyze or process. Meta also sees the technology as being useful for understanding webpage content, augmented reality applications, image editing, and aiding scientific study by automatically localizing animals or objects to track on video.
Typically, Meta says, creating an accurate segmentation model "requires highly specialized work by technical experts with access to AI training infrastructure and large volumes of carefully annotated in-domain data." By creating SAM, Meta hopes to "democratize" this process by reducing the need for specialized training and expertise, which it hopes will foster further research into computer vision. In addition to SAM, Meta has assembled a dataset it calls "SA-1B" that includes 11 million images licensed from "a large photo company" and 1.1 billion segmentation masks produced by its segmentation model. Meta will make SAM and its dataset available for research purposes under an Apache 2.0 license. Currently, the code (without the weights) is available on GitHub, and Meta has created a free interactive demo of its segmentation technology.
Typically, Meta says, creating an accurate segmentation model "requires highly specialized work by technical experts with access to AI training infrastructure and large volumes of carefully annotated in-domain data." By creating SAM, Meta hopes to "democratize" this process by reducing the need for specialized training and expertise, which it hopes will foster further research into computer vision. In addition to SAM, Meta has assembled a dataset it calls "SA-1B" that includes 11 million images licensed from "a large photo company" and 1.1 billion segmentation masks produced by its segmentation model. Meta will make SAM and its dataset available for research purposes under an Apache 2.0 license. Currently, the code (without the weights) is available on GitHub, and Meta has created a free interactive demo of its segmentation technology.
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