Segment Anything Model ( SAM ) by META AI | Image Segmentation | Object Detection | Karndeep Singh
The Segment Anything aims to democratize segmentation in computer vision by introducing a new task, dataset, and model for image segmentation. This core task is used in a broad array of applications, from analyzing scientific imagery to editing photos. However, creating an accurate segmentation model typically requires highly specialized work by technical experts with access to AI training infrastructure and large volumes of carefully annotated in-domain data.
To address this, the Segment Anything project is releasing both the Segment Anything Model (SAM) and the Segment Anything 1-Billion mask dataset (SA-1B), the largest ever segmentation dataset. SA-1B is available for research purposes, and SAM is available under a permissive open license (Apache 2.0). The project reduces the need for task-specific modeling expertise, training compute, and custom data annotation for image segmentation.
The Segment Anything Model is a general model trained on diverse data that can adapt to specific tasks. With the release of this project, we hope to enable a broad range of applications and foster further research into foundation models for computer vision. Check out our demo to try SAM with your own images and join us in our mission to democratize segmentation in computer vision.
Links:
1. SAM : https://segment-anything.com/
2. SAM Github: https://github.com/facebookresearch/s...
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3. Github: https://www.github.com/karndeepsingh
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#ai #imagesegmentation #computervision #objectdetection